In situ recycling is one of the most effective methods to dispose of earth pressure balance(EPB)shield waste muck with residual foaming agents with high moisture content.In this context,response surface methodology(RS...In situ recycling is one of the most effective methods to dispose of earth pressure balance(EPB)shield waste muck with residual foaming agents with high moisture content.In this context,response surface methodology(RSM)was employed to quantify the effects of independent variables,including flocculant dosage,defoamer dosage,and muck drying mass(MDM)and their interactions on defoaming-flocculation-dewatering indices.The polymeric aluminum chloride(PACL)and hydroxy silicone oil-glycerol polypropylene ether(H-G)were selected as the flocculant and defoamer.The contents of surfactants and foam stabilizers in residual foaming agents were determined using the proposed empirical equation.The defoaming ratio,antifoaming ratio,turbidity,moisture content,filtration loss ratio,and fall cone penetration depth were considered as dependent variables.The accuracy of developed RSM models was verified by the analysis results of variance,residuals,and paired t-test.Combined with the desirability approach,an optimal mixing ratio of 0.078 wt%PACL,0.016 wt%H-G,and 27.882 wt%MDM was recommended,leading to a defoaming ratio of 98.34 vol%for residual foams and a moisture content of 56.72 wt%for pressure-filtration cakes.Our findings were demonstrated to be able to provide useful guidance for prediction and optimization of the in situ recycling indicators of EPB shield waste muck in metro tunnel construction sites.展开更多
In this article, a novel scalarization technique, called the improved objective-constraint approach, is introduced to find efficient solutions of a given multiobjective programming problem. The presented scalarized pr...In this article, a novel scalarization technique, called the improved objective-constraint approach, is introduced to find efficient solutions of a given multiobjective programming problem. The presented scalarized problem extends the objective-constraint problem. It is demonstrated that how adding variables to the scalarized problem, can lead to find conditions for (weakly, properly) Pareto optimal solutions. Applying the obtained necessary and sufficient conditions, two algorithms for generating the Pareto front approximation of bi-objective and three-objective programming problems are designed. These algorithms are easy to implement and can achieve an even approximation of (weakly, properly) Pareto optimal solutions. These algorithms can be generalized for optimization problems with more than three criterion functions, too. The effectiveness and capability of the algorithms are demonstrated in test problems.展开更多
The Nesterov accelerated dynamical approach serves as an essential tool for addressing convex optimization problems with accelerated convergence rates.Most previous studies in this field have primarily concentrated on...The Nesterov accelerated dynamical approach serves as an essential tool for addressing convex optimization problems with accelerated convergence rates.Most previous studies in this field have primarily concentrated on unconstrained smooth con-vex optimization problems.In this paper,on the basis of primal-dual dynamical approach,Nesterov accelerated dynamical approach,projection operator and directional gradient,we present two accelerated primal-dual projection neurodynamic approaches with time scaling to address convex optimization problems with smooth and nonsmooth objective functions subject to linear and set constraints,which consist of a second-order ODE(ordinary differential equation)or differential conclusion system for the primal variables and a first-order ODE for the dual vari-ables.By satisfying specific conditions for time scaling,we demonstrate that the proposed approaches have a faster conver-gence rate.This only requires assuming convexity of the objective function.We validate the effectiveness of our proposed two accel-erated primal-dual projection neurodynamic approaches through numerical experiments.展开更多
In recent decades,fog computing has played a vital role in executing parallel computational tasks,specifically,scientific workflow tasks.In cloud data centers,fog computing takes more time to run workflow applications...In recent decades,fog computing has played a vital role in executing parallel computational tasks,specifically,scientific workflow tasks.In cloud data centers,fog computing takes more time to run workflow applications.Therefore,it is essential to develop effective models for Virtual Machine(VM)allocation and task scheduling in fog computing environments.Effective task scheduling,VM migration,and allocation,altogether optimize the use of computational resources across different fog nodes.This process ensures that the tasks are executed with minimal energy consumption,which reduces the chances of resource bottlenecks.In this manuscript,the proposed framework comprises two phases:(i)effective task scheduling using a fractional selectivity approach and(ii)VM allocation by proposing an algorithm by the name of Fitness Sharing Chaotic Particle Swarm Optimization(FSCPSO).The proposed FSCPSO algorithm integrates the concepts of chaos theory and fitness sharing that effectively balance both global exploration and local exploitation.This balance enables the use of a wide range of solutions that leads to minimal total cost and makespan,in comparison to other traditional optimization algorithms.The FSCPSO algorithm’s performance is analyzed using six evaluation measures namely,Load Balancing Level(LBL),Average Resource Utilization(ARU),total cost,makespan,energy consumption,and response time.In relation to the conventional optimization algorithms,the FSCPSO algorithm achieves a higher LBL of 39.12%,ARU of 58.15%,a minimal total cost of 1175,and a makespan of 85.87 ms,particularly when evaluated for 50 tasks.展开更多
The majority of topology optimization of compliant mechanisms uses linear finite element models to find the structure responses.Because the displacements of compliant mechanisms are intrinsically large,the topological...The majority of topology optimization of compliant mechanisms uses linear finite element models to find the structure responses.Because the displacements of compliant mechanisms are intrinsically large,the topological design can not provide quantitatively accurate result.Thus,topological design of these mechanisms considering geometrical nonlinearities is essential.A new methodology for geometrical nonlinear topology optimization of compliant mechanisms under displacement loading is presented.Frame elements are chosen to represent the design domain because they are capable of capturing the bending modes.Geometrically nonlinear structural response is obtained by using the co-rotational total Lagrange finite element formulation,and the equilibrium is solved by using the incremental scheme combined with Newton-Raphson iteration.The multi-objective function is developed by the minimum strain energy and maximum geometric advantage to design the mechanism which meets both stiffness and flexibility requirements, respectively.The adjoint method and the direct differentiation method are applied to obtain the sensitivities of the objective functions. The method of moving asymptotes（MMA） is employed as optimizer.The numerical example is simulated to show that the optimal mechanism based on geometrically nonlinear formulation not only has more flexibility and stiffness than that based on linear formulation,but also has better stress distribution than the one.It is necessary to design compliant mechanisms using geometrically nonlinear topology optimization.Compared with linear formulation,the formulation for geometrically nonlinear topology optimization of compliant mechanisms can give the compliant mechanism that has better mechanical performance.A new method is provided for topological design of large displacement compliant mechanisms.展开更多
A sequential statistical approach was applied to optimizing the fermentation medium of epothilones（Epos） production by means of a mutant which was obtained by treating polyangium cellulosum ATCC 15384 with nitrite a...A sequential statistical approach was applied to optimizing the fermentation medium of epothilones（Epos） production by means of a mutant which was obtained by treating polyangium cellulosum ATCC 15384 with nitrite and ultraviolet. The effects of different carbon sources and nitrogen sources on the fermentation medium were tested, and the suitable ones were selected. Then a uniform design was employed to design the experiments. A linear model was developed for identifying the significant components in fermentation medium, while a third degree polynomial model was used for studying the relationship between the concentration of the components in fermentation medium and the yield of Epos（YEPs）. A pattern search method was used for searching the optimum fermentation medium in the test space, which was as follows（g/L）： potassium nitrate 8.00, soybean peptone 17.60, potassium hydrogen phos- phate 1.00, beef extraction 6.46, yeast extraction 1.00, calcium chloride 0.25, sodium chloride 1.00 and ferric chloride 0.02. The optimum fermentation medium was expected to result in a yield of Epos（YEPs） of 2.48 mg/L. The validation experiments with the optimum medium were performed in triplicate and the average yield of Epos was 2.45 mg/L which was 7.78 times higher than that of Epos prepared without optimization.展开更多
In view of the fact that the follow-up search for an optimal topology is affected by deleting a large number of high-relative-density elements. When the typical density interpolation approach, namely, solid isotropic ...In view of the fact that the follow-up search for an optimal topology is affected by deleting a large number of high-relative-density elements. When the typical density interpolation approach, namely, solid isotropic microstructures with penalization （SIMP）, is employed in the continuum structural topology optimization, a new density interpolation approach based on the logistic function is proposed in this paper. This method can weaken low-relative-density elements while enhancing high-relative-density elements by polarization, and then rationally realize polarization of the intermediate density elements. It can reduce the number of gray-scale elements as much as possible to get the optimal topology with distinct boundaries in conjunction with the sensitivity filtering method based on particle swarm optimization （PSO）. Several typical numerical examples are given to demonstrate this method.展开更多
Biodiesel is an alternative renewable fuel which is produced by using biomass resources. Its physicochemical properties are close to those of the petroleum diesel fuel. This study highlights biodiesel production from ...Biodiesel is an alternative renewable fuel which is produced by using biomass resources. Its physicochemical properties are close to those of the petroleum diesel fuel. This study highlights biodiesel production from safflower seed oil. The main aim of this experimental work is to optimize the process parameters, namely the methanolto-oil molar ratio, catalyst concentration, reaction time and reaction temperature for biodiesel production. The Taguchi robust design approach was used with an L9 orthogonal array to analyze the influence of process factors on performance parameters. The results showed that the optimum yield of biodiesel was 93.8% with viscosity 5.60 c St, with a methanol-to-oil molar ratio of 4:1, catalyst concentration of 1.5 wt%, reaction time of 90 min and reaction temperature of 60 ℃. The catalyst concentration was found to be the most influencing parameter which contributed 51.1% and 50.8% of the total effect on the yield of biodiesel, Y;, and viscosity of biodiesel, Y;, respectively.展开更多
In the present paper,a so-called epsilon-continuation approach is proposed for the solution of singular optimum in truss topology optimization problems.This approach is an improved version of the epsilon-relaxed appro...In the present paper,a so-called epsilon-continuation approach is proposed for the solution of singular optimum in truss topology optimization problems.This approach is an improved version of the epsilon-relaxed approach developed by the authors previously.In the proposed approach, we start the optimization process from a relaxation parameter with a relatively large value and obtain a solution by applying the epsilon-relaxed approach.Then we decrease the value of the relaxation parameter by a small amount and choose the optimal solution found from the previous optimization process as the initial design for the next optimization.This continuation process is continued until a small termination value of the relaxation parameter is reached.Convergence analysis of the proposed approach is also presented.Numerical examples show that this approach can alleviate the dependence of the final solution on the initial choice of the design variable and enhance the probability of finding the singular optimum from rather arbitrary initial designs.展开更多
A comparison of arithmetic operations of two dynamic process optimization approaches called quasi-sequential approach and reduced Sequential Quadratic Programming(rSQP)simultaneous approach with respect to equality co...A comparison of arithmetic operations of two dynamic process optimization approaches called quasi-sequential approach and reduced Sequential Quadratic Programming(rSQP)simultaneous approach with respect to equality constrained optimization problems is presented.Through the detail comparison of arithmetic operations,it is concluded that the average iteration number within differential algebraic equations(DAEs)integration of quasi-sequential approach could be regarded as a criterion.One formula is given to calculate the threshold value of average iteration number.If the average iteration number is less than the threshold value,quasi-sequential approach takes advantage of rSQP simultaneous approach which is more suitable contrarily.Two optimal control problems are given to demonstrate the usage of threshold value.For optimal control problems whose objective is to stay near desired operating point,the iteration number is usually small.Therefore,quasi-sequential approach seems more suitable for such problems.展开更多
Rechargeable magnesium-ion batteries(MIBs) are favorable substitutes for conventional lithium-ion batteries(LIBs) because of abundant magnesium reserves, a high theoretical energy density, and great inherent safety. O...Rechargeable magnesium-ion batteries(MIBs) are favorable substitutes for conventional lithium-ion batteries(LIBs) because of abundant magnesium reserves, a high theoretical energy density, and great inherent safety. Organic electrode materials with excellent structural tunability,unique coordination reaction mechanisms, and environmental friendliness offer great potential to promote the electrochemical performance of MIBs. However, research on organic magnesium battery cathode materials is still preliminary with many significant challenges to be resolved including low electrical conductivity and unwanted but severe dissolution in useful electrolytes. Herein, we provide a detailed overview of reported organic cathode materials for MIBs. We begin with basic properties such as charge storage mechanisms(e.g., n-, p-, and bipolartype), moving to recent advances in various types of organic cathodes including carbonyl-, nitrogen-, and sulfur-based materials. To shed light on the diverse strategies targeting high-performance Mg-organic batteries, elaborate summaries of various approaches are presented.Generally, these strategies include molecular design, polymerization, mixing with carbon, nanosizing and electrolyte/separator optimization.This review provides insights on exploring high-performance organic cathodes in rechargeable MIBs.展开更多
The large-scale optimization problem requires some optimization techniques, and the Metaheuristics approach is highly useful for solving difficult optimization problems in practice. The purpose of the research is to o...The large-scale optimization problem requires some optimization techniques, and the Metaheuristics approach is highly useful for solving difficult optimization problems in practice. The purpose of the research is to optimize the transportation system with the help of this approach. We selected forest vehicle routing data as the case study to minimize the total cost and the distance of the forest transportation system. Matlab software helps us find the best solution for this case by applying three algorithms of Metaheuristics: Genetic Algorithm (GA), Ant Colony Optimization (ACO), and Extended Great Deluge (EGD). The results show that GA, compared to ACO and EGD, provides the best solution for the cost and the length of our case study. EGD is the second preferred approach, and ACO offers the last solution.展开更多
We present a new aerodynamic design method based on the lattice Boltzmann method （LBM） and the adjoint approach. The flow field and the adjoint equation are numerically simulated by the GILBM （generalized form of i...We present a new aerodynamic design method based on the lattice Boltzmann method （LBM） and the adjoint approach. The flow field and the adjoint equation are numerically simulated by the GILBM （generalized form of interpolation supplemented LBM） on non-uniform meshes. The first-order approximation for the equilibrium dis- tribution function on the boundary is proposed to diminish the singularity of boundary conditions. Further, a new treatment of the solid boundary in the LBM is described par- ticularly for the airfoil optimization design problem. For a given objective function, the adjoint equation and its boundary conditions are derived analytically. The feasibility and accuracy of the new approach have been perfectly validated by the design optimization of NACA0012 airfoil.展开更多
In the Acoustics channel,it is incredibly challenging to offer data transfer for time-sourced applications in an energy-efficient manner due to higher error rate and propagation delay.Subsequently,conventional re-tran...In the Acoustics channel,it is incredibly challenging to offer data transfer for time-sourced applications in an energy-efficient manner due to higher error rate and propagation delay.Subsequently,conventional re-transmission over any failure generally initiates significantly larger end-to-end delay,and therefore it is not probable for time-based services.Moreover,standard techniques without any re-transmission consume enormous energy.This investigation proposes a novel multi-hop energy-aware transmission-based intelligent water wave optimization strategy.It ensures reduced end-to-end while attaining potential amongst overall energy efficiency end-to-end packet delay.It merges a naturally inspired meta-heuristic approach with multi-hop routing for data packets to reach the destination.The appropriate design of this Meta heuristic-based energy-aware scheme consumes lesser energy than the conventional one-hop transmission strategy without re-transmission.However,there is no hop-by-hop re-transmission facilitated.The proposed model shows only lesser delay than conventional methods with re-transmission.This work facilitates extensive work to carry out the proposed model performance with the MATLAB simulation environment.The results illustrate that the model is exceptionally energyefficient with lesser packet delays.With 500 nodes,the packet delivery ratio of proposed model is 100%,average delay is reduced by 2%,total energy consumption is 8 J,average packet redundancy is 1.856,and idle energy is 6.9Mwh.The proposed model outperforms existing approaches like OSF,AOR,and DMR respectively.展开更多
The minimum vertex cover problem(MVCP)is a well-known combinatorial optimization problem of graph theory.The MVCP is an NP(nondeterministic polynomial)complete problem and it has an exponential growing complexity with...The minimum vertex cover problem(MVCP)is a well-known combinatorial optimization problem of graph theory.The MVCP is an NP(nondeterministic polynomial)complete problem and it has an exponential growing complexity with respect to the size of a graph.No algorithm exits till date that can exactly solve the problem in a deterministic polynomial time scale.However,several algorithms are proposed that solve the problem approximately in a short polynomial time scale.Such algorithms are useful for large size graphs,for which exact solution of MVCP is impossible with current computational resources.The MVCP has a wide range of applications in the fields like bioinformatics,biochemistry,circuit design,electrical engineering,data aggregation,networking,internet traffic monitoring,pattern recognition,marketing and franchising etc.This work aims to solve the MVCP approximately by a novel graph decomposition approach.The decomposition of the graph yields a subgraph that contains edges shared by triangular edge structures.A subgraph is covered to yield a subgraph that forms one or more Hamiltonian cycles or paths.In order to reduce complexity of the algorithm a new strategy is also proposed.The reduction strategy can be used for any algorithm solving MVCP.Based on the graph decomposition and the reduction strategy,two algorithms are formulated to approximately solve the MVCP.These algorithms are tested using well known standard benchmark graphs.The key feature of the results is a good approximate error ratio and improvement in optimum vertex cover values for few graphs.展开更多
In the current scenario of global competition and short product life cycles, customer-defined satisfaction has attracted interest in artifact design. Accordingly, intelligent decision-making through multi-objective op...In the current scenario of global competition and short product life cycles, customer-defined satisfaction has attracted interest in artifact design. Accordingly, intelligent decision-making through multi-objective optimization has been proposed as an efficient method for human-centered manufacturing. However, previous vast researches on optimization have been mainly focused on optimization theory and optimization techniques and paid little interests on the process of problem formulation itself. In this paper, therefore, the authors present a total framework for supporting multi-objective decision making. Then, the authors try to solve the formulated multi-objective optimization problem that involves both qualitative and quantitative performance measures as a general consequence from the above procedure. Taking especially quality as a qualitative measure, the authors gave a new idea to evaluate the quality quantitatively. Additionally, to facilitate the portability of the proposed method in multidisciplinary decision-making environments, the authors implement the proposal algorithm in an Excel spreadsheet and validate the effectiveness of the approach through a case study.展开更多
The paper is devoted to H-optimization problems for linear time invariant(LTI) systems with scalar control, external disturbance and measurement noise. All these problems can be numerically solved with the help of the...The paper is devoted to H-optimization problems for linear time invariant(LTI) systems with scalar control, external disturbance and measurement noise. All these problems can be numerically solved with the help of the well-known universal approaches based on Riccati equations, linear matrix inequalities(LMI) or maximum entropy technique. Nevertheless, in our opinion there exists a possibility to increase the computational efficiency of synthesis using a special spectral approach to the above mentioned problems in frequency domain. Some relevant details are discussed and efficient numerical algorithms are proposed for the practical implementation of spectral approach. One of its virtues is a possibility to present optimal solutions in a specific form, which is convenient for investigation.展开更多
We present main ideas of a recently proposed method for interactive multiobjective optimization,which is based on application of a logical preference model built using the Dominance-based Rough Set Approach(DRSA).
Phononic materials with specific band-gap characteristics at desired frequency ranges are in great demand for vibration and noise isolation, elastic wave filters, and acoustic devices. The attenuation coefficient curv...Phononic materials with specific band-gap characteristics at desired frequency ranges are in great demand for vibration and noise isolation, elastic wave filters, and acoustic devices. The attenuation coefficient curve depicts both the frequency range of band gap and the attenuation of elastic wave, where the frequency ranges corresponding to the none-zero attenuation coefficients are band gaps. Therefore, the band-gap characteristics can be achieved through maximizing the attenuation coefficient at the corresponding frequency or within the corresponding frequency range. Because the attenuation coefficient curve is not smooth in the frequency domain, the gradient-based optimization methods cannot be directly used in the design optimization of phononic band-gap materials to achieve the maximum attenuation within the desired frequency range. To overcome this difficulty, the objective of maximizing the attenuation coefficient is transformed into maximizing its Cosine, and in this way, the objective function is smoothed and becomes differentiable. Based on this objective function, a novel gradient-based optimization approach is proposed to open the band gap at a prescribed frequency range and to further maximize the attenuation efficiency of the elastic wave at a specific frequency or within a prescribed frequency range. Numerical results demonstrate the effectiveness of the proposed gradient-based optimization method for enhancing the wave attenuation properties.展开更多
A multi-objective scheme for structural topology optimization of distributed compliant mechanisms of micro-actuators in MEMS condition is presented in this work, in which mechanical flexibility and structural stiffnes...A multi-objective scheme for structural topology optimization of distributed compliant mechanisms of micro-actuators in MEMS condition is presented in this work, in which mechanical flexibility and structural stiffness are both considered as objective functions. The compliant micro-mechanism developed in this way can not only provide sufficient output work but also have sufficient rigidity to resist reaction forces and maintain its shape when holding the work-piece. A density filtering approach is also proposed to eliminate numerical instabilities such as checkerboards, mesh-dependency and one-node connected hinges occurring in resulting mechanisms. SIMP is used as the interpolation scheme to indicate the dependence of material modulus on element-regularized densities. The sequential convex programming method, such as the method of moving asymptotes （MMA）, is used to solve the optimization problem. The validation of the presented methodologies is demonstrated by a typical numerical example.展开更多
基金supported by the National Youth Top-notch Talent Support Program of China(Grant No.00389335)the National Natural Science Foundation of China(Grant No.52378392)the“Foal Eagle Program”Youth Top-notch Talent Project of Fujian Province(Grant No.00387088).
文摘In situ recycling is one of the most effective methods to dispose of earth pressure balance(EPB)shield waste muck with residual foaming agents with high moisture content.In this context,response surface methodology(RSM)was employed to quantify the effects of independent variables,including flocculant dosage,defoamer dosage,and muck drying mass(MDM)and their interactions on defoaming-flocculation-dewatering indices.The polymeric aluminum chloride(PACL)and hydroxy silicone oil-glycerol polypropylene ether(H-G)were selected as the flocculant and defoamer.The contents of surfactants and foam stabilizers in residual foaming agents were determined using the proposed empirical equation.The defoaming ratio,antifoaming ratio,turbidity,moisture content,filtration loss ratio,and fall cone penetration depth were considered as dependent variables.The accuracy of developed RSM models was verified by the analysis results of variance,residuals,and paired t-test.Combined with the desirability approach,an optimal mixing ratio of 0.078 wt%PACL,0.016 wt%H-G,and 27.882 wt%MDM was recommended,leading to a defoaming ratio of 98.34 vol%for residual foams and a moisture content of 56.72 wt%for pressure-filtration cakes.Our findings were demonstrated to be able to provide useful guidance for prediction and optimization of the in situ recycling indicators of EPB shield waste muck in metro tunnel construction sites.
文摘In this article, a novel scalarization technique, called the improved objective-constraint approach, is introduced to find efficient solutions of a given multiobjective programming problem. The presented scalarized problem extends the objective-constraint problem. It is demonstrated that how adding variables to the scalarized problem, can lead to find conditions for (weakly, properly) Pareto optimal solutions. Applying the obtained necessary and sufficient conditions, two algorithms for generating the Pareto front approximation of bi-objective and three-objective programming problems are designed. These algorithms are easy to implement and can achieve an even approximation of (weakly, properly) Pareto optimal solutions. These algorithms can be generalized for optimization problems with more than three criterion functions, too. The effectiveness and capability of the algorithms are demonstrated in test problems.
基金supported by the National Natural Science Foundation of China(62176218,62176027)the Fundamental Research Funds for the Central Universities(XDJK2020TY003)the Funds for Chongqing Talent Plan(cstc2024ycjh-bgzxm0082)。
文摘The Nesterov accelerated dynamical approach serves as an essential tool for addressing convex optimization problems with accelerated convergence rates.Most previous studies in this field have primarily concentrated on unconstrained smooth con-vex optimization problems.In this paper,on the basis of primal-dual dynamical approach,Nesterov accelerated dynamical approach,projection operator and directional gradient,we present two accelerated primal-dual projection neurodynamic approaches with time scaling to address convex optimization problems with smooth and nonsmooth objective functions subject to linear and set constraints,which consist of a second-order ODE(ordinary differential equation)or differential conclusion system for the primal variables and a first-order ODE for the dual vari-ables.By satisfying specific conditions for time scaling,we demonstrate that the proposed approaches have a faster conver-gence rate.This only requires assuming convexity of the objective function.We validate the effectiveness of our proposed two accel-erated primal-dual projection neurodynamic approaches through numerical experiments.
基金This work was supported in part by the National Science and Technology Council of Taiwan,under Contract NSTC 112-2410-H-324-001-MY2.
文摘In recent decades,fog computing has played a vital role in executing parallel computational tasks,specifically,scientific workflow tasks.In cloud data centers,fog computing takes more time to run workflow applications.Therefore,it is essential to develop effective models for Virtual Machine(VM)allocation and task scheduling in fog computing environments.Effective task scheduling,VM migration,and allocation,altogether optimize the use of computational resources across different fog nodes.This process ensures that the tasks are executed with minimal energy consumption,which reduces the chances of resource bottlenecks.In this manuscript,the proposed framework comprises two phases:(i)effective task scheduling using a fractional selectivity approach and(ii)VM allocation by proposing an algorithm by the name of Fitness Sharing Chaotic Particle Swarm Optimization(FSCPSO).The proposed FSCPSO algorithm integrates the concepts of chaos theory and fitness sharing that effectively balance both global exploration and local exploitation.This balance enables the use of a wide range of solutions that leads to minimal total cost and makespan,in comparison to other traditional optimization algorithms.The FSCPSO algorithm’s performance is analyzed using six evaluation measures namely,Load Balancing Level(LBL),Average Resource Utilization(ARU),total cost,makespan,energy consumption,and response time.In relation to the conventional optimization algorithms,the FSCPSO algorithm achieves a higher LBL of 39.12%,ARU of 58.15%,a minimal total cost of 1175,and a makespan of 85.87 ms,particularly when evaluated for 50 tasks.
基金supported by National Science Foundation for Distinguished Young Scholars of China(Grant No.50825504)National Natural Science Foundation of China(Grant No.50775073)United Fund of Natural Science Foundation of China and Guangdong Province (Grant No.U0934004)
文摘The majority of topology optimization of compliant mechanisms uses linear finite element models to find the structure responses.Because the displacements of compliant mechanisms are intrinsically large,the topological design can not provide quantitatively accurate result.Thus,topological design of these mechanisms considering geometrical nonlinearities is essential.A new methodology for geometrical nonlinear topology optimization of compliant mechanisms under displacement loading is presented.Frame elements are chosen to represent the design domain because they are capable of capturing the bending modes.Geometrically nonlinear structural response is obtained by using the co-rotational total Lagrange finite element formulation,and the equilibrium is solved by using the incremental scheme combined with Newton-Raphson iteration.The multi-objective function is developed by the minimum strain energy and maximum geometric advantage to design the mechanism which meets both stiffness and flexibility requirements, respectively.The adjoint method and the direct differentiation method are applied to obtain the sensitivities of the objective functions. The method of moving asymptotes（MMA） is employed as optimizer.The numerical example is simulated to show that the optimal mechanism based on geometrically nonlinear formulation not only has more flexibility and stiffness than that based on linear formulation,but also has better stress distribution than the one.It is necessary to design compliant mechanisms using geometrically nonlinear topology optimization.Compared with linear formulation,the formulation for geometrically nonlinear topology optimization of compliant mechanisms can give the compliant mechanism that has better mechanical performance.A new method is provided for topological design of large displacement compliant mechanisms.
基金Supported by the Science Technology Development Project of Jilin Province,China(No.20020503-2)
文摘A sequential statistical approach was applied to optimizing the fermentation medium of epothilones（Epos） production by means of a mutant which was obtained by treating polyangium cellulosum ATCC 15384 with nitrite and ultraviolet. The effects of different carbon sources and nitrogen sources on the fermentation medium were tested, and the suitable ones were selected. Then a uniform design was employed to design the experiments. A linear model was developed for identifying the significant components in fermentation medium, while a third degree polynomial model was used for studying the relationship between the concentration of the components in fermentation medium and the yield of Epos（YEPs）. A pattern search method was used for searching the optimum fermentation medium in the test space, which was as follows（g/L）： potassium nitrate 8.00, soybean peptone 17.60, potassium hydrogen phos- phate 1.00, beef extraction 6.46, yeast extraction 1.00, calcium chloride 0.25, sodium chloride 1.00 and ferric chloride 0.02. The optimum fermentation medium was expected to result in a yield of Epos（YEPs） of 2.48 mg/L. The validation experiments with the optimum medium were performed in triplicate and the average yield of Epos was 2.45 mg/L which was 7.78 times higher than that of Epos prepared without optimization.
基金supported by the National Natural Science Foundation of China(No.51105229)the National Science Foundation for Distinguished Young Scholars of Hubei Province of China(No.2013CFA022)+1 种基金the Science and Technology Support Program of Hubei Province of China(N0.2015BHE026)the Fund Project of Outstanding Dissertation of China Three Gorges University(No.2014PY026)
文摘In view of the fact that the follow-up search for an optimal topology is affected by deleting a large number of high-relative-density elements. When the typical density interpolation approach, namely, solid isotropic microstructures with penalization （SIMP）, is employed in the continuum structural topology optimization, a new density interpolation approach based on the logistic function is proposed in this paper. This method can weaken low-relative-density elements while enhancing high-relative-density elements by polarization, and then rationally realize polarization of the intermediate density elements. It can reduce the number of gray-scale elements as much as possible to get the optimal topology with distinct boundaries in conjunction with the sensitivity filtering method based on particle swarm optimization （PSO）. Several typical numerical examples are given to demonstrate this method.
文摘Biodiesel is an alternative renewable fuel which is produced by using biomass resources. Its physicochemical properties are close to those of the petroleum diesel fuel. This study highlights biodiesel production from safflower seed oil. The main aim of this experimental work is to optimize the process parameters, namely the methanolto-oil molar ratio, catalyst concentration, reaction time and reaction temperature for biodiesel production. The Taguchi robust design approach was used with an L9 orthogonal array to analyze the influence of process factors on performance parameters. The results showed that the optimum yield of biodiesel was 93.8% with viscosity 5.60 c St, with a methanol-to-oil molar ratio of 4:1, catalyst concentration of 1.5 wt%, reaction time of 90 min and reaction temperature of 60 ℃. The catalyst concentration was found to be the most influencing parameter which contributed 51.1% and 50.8% of the total effect on the yield of biodiesel, Y;, and viscosity of biodiesel, Y;, respectively.
基金The project supported by the National Natural Science Foundation of China (10102003,10032010 and 10032030)
文摘In the present paper,a so-called epsilon-continuation approach is proposed for the solution of singular optimum in truss topology optimization problems.This approach is an improved version of the epsilon-relaxed approach developed by the authors previously.In the proposed approach, we start the optimization process from a relaxation parameter with a relatively large value and obtain a solution by applying the epsilon-relaxed approach.Then we decrease the value of the relaxation parameter by a small amount and choose the optimal solution found from the previous optimization process as the initial design for the next optimization.This continuation process is continued until a small termination value of the relaxation parameter is reached.Convergence analysis of the proposed approach is also presented.Numerical examples show that this approach can alleviate the dependence of the final solution on the initial choice of the design variable and enhance the probability of finding the singular optimum from rather arbitrary initial designs.
基金Supported by the National Natural Science Foundation of China（20676117） the National Creative Research Groups Science Foundation of China（60421002）
文摘A comparison of arithmetic operations of two dynamic process optimization approaches called quasi-sequential approach and reduced Sequential Quadratic Programming(rSQP)simultaneous approach with respect to equality constrained optimization problems is presented.Through the detail comparison of arithmetic operations,it is concluded that the average iteration number within differential algebraic equations(DAEs)integration of quasi-sequential approach could be regarded as a criterion.One formula is given to calculate the threshold value of average iteration number.If the average iteration number is less than the threshold value,quasi-sequential approach takes advantage of rSQP simultaneous approach which is more suitable contrarily.Two optimal control problems are given to demonstrate the usage of threshold value.For optimal control problems whose objective is to stay near desired operating point,the iteration number is usually small.Therefore,quasi-sequential approach seems more suitable for such problems.
基金the support from the National Key Research & Development Program (2022YFB3803700) of ChinaNational Natural Science Foundation (No.52171186)the support from the Center of Hydrogen Science,Shanghai Jiao Tong University。
文摘Rechargeable magnesium-ion batteries(MIBs) are favorable substitutes for conventional lithium-ion batteries(LIBs) because of abundant magnesium reserves, a high theoretical energy density, and great inherent safety. Organic electrode materials with excellent structural tunability,unique coordination reaction mechanisms, and environmental friendliness offer great potential to promote the electrochemical performance of MIBs. However, research on organic magnesium battery cathode materials is still preliminary with many significant challenges to be resolved including low electrical conductivity and unwanted but severe dissolution in useful electrolytes. Herein, we provide a detailed overview of reported organic cathode materials for MIBs. We begin with basic properties such as charge storage mechanisms(e.g., n-, p-, and bipolartype), moving to recent advances in various types of organic cathodes including carbonyl-, nitrogen-, and sulfur-based materials. To shed light on the diverse strategies targeting high-performance Mg-organic batteries, elaborate summaries of various approaches are presented.Generally, these strategies include molecular design, polymerization, mixing with carbon, nanosizing and electrolyte/separator optimization.This review provides insights on exploring high-performance organic cathodes in rechargeable MIBs.
文摘The large-scale optimization problem requires some optimization techniques, and the Metaheuristics approach is highly useful for solving difficult optimization problems in practice. The purpose of the research is to optimize the transportation system with the help of this approach. We selected forest vehicle routing data as the case study to minimize the total cost and the distance of the forest transportation system. Matlab software helps us find the best solution for this case by applying three algorithms of Metaheuristics: Genetic Algorithm (GA), Ant Colony Optimization (ACO), and Extended Great Deluge (EGD). The results show that GA, compared to ACO and EGD, provides the best solution for the cost and the length of our case study. EGD is the second preferred approach, and ACO offers the last solution.
基金Project supported by the National Basic Research Program of China(No.2014CB744100)the National Natural Science Foundation of China(Nos.61403245 and 91648119)the Shanghai Municipal Science and Technology Commision(No.14500500400)
文摘We present a new aerodynamic design method based on the lattice Boltzmann method （LBM） and the adjoint approach. The flow field and the adjoint equation are numerically simulated by the GILBM （generalized form of interpolation supplemented LBM） on non-uniform meshes. The first-order approximation for the equilibrium dis- tribution function on the boundary is proposed to diminish the singularity of boundary conditions. Further, a new treatment of the solid boundary in the LBM is described par- ticularly for the airfoil optimization design problem. For a given objective function, the adjoint equation and its boundary conditions are derived analytically. The feasibility and accuracy of the new approach have been perfectly validated by the design optimization of NACA0012 airfoil.
文摘In the Acoustics channel,it is incredibly challenging to offer data transfer for time-sourced applications in an energy-efficient manner due to higher error rate and propagation delay.Subsequently,conventional re-transmission over any failure generally initiates significantly larger end-to-end delay,and therefore it is not probable for time-based services.Moreover,standard techniques without any re-transmission consume enormous energy.This investigation proposes a novel multi-hop energy-aware transmission-based intelligent water wave optimization strategy.It ensures reduced end-to-end while attaining potential amongst overall energy efficiency end-to-end packet delay.It merges a naturally inspired meta-heuristic approach with multi-hop routing for data packets to reach the destination.The appropriate design of this Meta heuristic-based energy-aware scheme consumes lesser energy than the conventional one-hop transmission strategy without re-transmission.However,there is no hop-by-hop re-transmission facilitated.The proposed model shows only lesser delay than conventional methods with re-transmission.This work facilitates extensive work to carry out the proposed model performance with the MATLAB simulation environment.The results illustrate that the model is exceptionally energyefficient with lesser packet delays.With 500 nodes,the packet delivery ratio of proposed model is 100%,average delay is reduced by 2%,total energy consumption is 8 J,average packet redundancy is 1.856,and idle energy is 6.9Mwh.The proposed model outperforms existing approaches like OSF,AOR,and DMR respectively.
文摘The minimum vertex cover problem(MVCP)is a well-known combinatorial optimization problem of graph theory.The MVCP is an NP(nondeterministic polynomial)complete problem and it has an exponential growing complexity with respect to the size of a graph.No algorithm exits till date that can exactly solve the problem in a deterministic polynomial time scale.However,several algorithms are proposed that solve the problem approximately in a short polynomial time scale.Such algorithms are useful for large size graphs,for which exact solution of MVCP is impossible with current computational resources.The MVCP has a wide range of applications in the fields like bioinformatics,biochemistry,circuit design,electrical engineering,data aggregation,networking,internet traffic monitoring,pattern recognition,marketing and franchising etc.This work aims to solve the MVCP approximately by a novel graph decomposition approach.The decomposition of the graph yields a subgraph that contains edges shared by triangular edge structures.A subgraph is covered to yield a subgraph that forms one or more Hamiltonian cycles or paths.In order to reduce complexity of the algorithm a new strategy is also proposed.The reduction strategy can be used for any algorithm solving MVCP.Based on the graph decomposition and the reduction strategy,two algorithms are formulated to approximately solve the MVCP.These algorithms are tested using well known standard benchmark graphs.The key feature of the results is a good approximate error ratio and improvement in optimum vertex cover values for few graphs.
文摘In the current scenario of global competition and short product life cycles, customer-defined satisfaction has attracted interest in artifact design. Accordingly, intelligent decision-making through multi-objective optimization has been proposed as an efficient method for human-centered manufacturing. However, previous vast researches on optimization have been mainly focused on optimization theory and optimization techniques and paid little interests on the process of problem formulation itself. In this paper, therefore, the authors present a total framework for supporting multi-objective decision making. Then, the authors try to solve the formulated multi-objective optimization problem that involves both qualitative and quantitative performance measures as a general consequence from the above procedure. Taking especially quality as a qualitative measure, the authors gave a new idea to evaluate the quality quantitatively. Additionally, to facilitate the portability of the proposed method in multidisciplinary decision-making environments, the authors implement the proposal algorithm in an Excel spreadsheet and validate the effectiveness of the approach through a case study.
基金supported by the Russian Foundation for Basic Research (RFBR), that controlled by the Government of Russian Federation (No. 17-07-00361)
文摘The paper is devoted to H-optimization problems for linear time invariant(LTI) systems with scalar control, external disturbance and measurement noise. All these problems can be numerically solved with the help of the well-known universal approaches based on Riccati equations, linear matrix inequalities(LMI) or maximum entropy technique. Nevertheless, in our opinion there exists a possibility to increase the computational efficiency of synthesis using a special spectral approach to the above mentioned problems in frequency domain. Some relevant details are discussed and efficient numerical algorithms are proposed for the practical implementation of spectral approach. One of its virtues is a possibility to present optimal solutions in a specific form, which is convenient for investigation.
文摘We present main ideas of a recently proposed method for interactive multiobjective optimization,which is based on application of a logical preference model built using the Dominance-based Rough Set Approach(DRSA).
基金Project supported by the National Natural Science Foundation of China(Nos.11502043,11332004 and 11402046)the Fundamental Research Funds for the Central Universities Of China(DUT15ZD101)the 111 Project(B14013)
文摘Phononic materials with specific band-gap characteristics at desired frequency ranges are in great demand for vibration and noise isolation, elastic wave filters, and acoustic devices. The attenuation coefficient curve depicts both the frequency range of band gap and the attenuation of elastic wave, where the frequency ranges corresponding to the none-zero attenuation coefficients are band gaps. Therefore, the band-gap characteristics can be achieved through maximizing the attenuation coefficient at the corresponding frequency or within the corresponding frequency range. Because the attenuation coefficient curve is not smooth in the frequency domain, the gradient-based optimization methods cannot be directly used in the design optimization of phononic band-gap materials to achieve the maximum attenuation within the desired frequency range. To overcome this difficulty, the objective of maximizing the attenuation coefficient is transformed into maximizing its Cosine, and in this way, the objective function is smoothed and becomes differentiable. Based on this objective function, a novel gradient-based optimization approach is proposed to open the band gap at a prescribed frequency range and to further maximize the attenuation efficiency of the elastic wave at a specific frequency or within a prescribed frequency range. Numerical results demonstrate the effectiveness of the proposed gradient-based optimization method for enhancing the wave attenuation properties.
基金Project supported by the National '973' Key Fundamental Research Project of China (No. 2003CB716207) the National '863' High-Tech Development Project of China (No.2003AA001031).
文摘A multi-objective scheme for structural topology optimization of distributed compliant mechanisms of micro-actuators in MEMS condition is presented in this work, in which mechanical flexibility and structural stiffness are both considered as objective functions. The compliant micro-mechanism developed in this way can not only provide sufficient output work but also have sufficient rigidity to resist reaction forces and maintain its shape when holding the work-piece. A density filtering approach is also proposed to eliminate numerical instabilities such as checkerboards, mesh-dependency and one-node connected hinges occurring in resulting mechanisms. SIMP is used as the interpolation scheme to indicate the dependence of material modulus on element-regularized densities. The sequential convex programming method, such as the method of moving asymptotes （MMA）, is used to solve the optimization problem. The validation of the presented methodologies is demonstrated by a typical numerical example.
