In terms of tandem cold mill productivity and product quality, a multi-objective optimization model of rolling schedule based on cost fimction was proposed to determine the stand reductions, inter-stand tensions and r...In terms of tandem cold mill productivity and product quality, a multi-objective optimization model of rolling schedule based on cost fimction was proposed to determine the stand reductions, inter-stand tensions and rolling speeds for a specified product. The proposed schedule optimization model consists of several single cost fi.mctions, which take rolling force, motor power, inter-stand tension and stand reduction into consideration. The cost function, which can evaluate how far the rolling parameters are from the ideal values, was minimized using the Nelder-Mead simplex method. The proposed rolling schedule optimization method has been applied successfully to the 5-stand tandem cold mill in Tangsteel, and the results from a case study show that the proposed method is superior to those based on empirical formulae.展开更多
In the last decade,space solar power satellites(SSPSs)have been conceived to support net-zero carbon emissions and have attracted considerable attention.Electric energy is transmitted to the ground via a microwave pow...In the last decade,space solar power satellites(SSPSs)have been conceived to support net-zero carbon emissions and have attracted considerable attention.Electric energy is transmitted to the ground via a microwave power beam,a technology known as microwave power transmission(MPT).Due to the vast transmission distance of tens of thousands of kilometers,the power transmitting antenna array must span up to 1 kilometer in diameter.At the same time,the size of the rectifying array on the ground should extend over a few kilometers.This makes the MPT system of SSPSs significantly larger than the existing aerospace engineering system.To design and operate a rational MPT system,comprehensive optimization is required.Taking the space MPT system engineering into consideration,a novel multi-objective optimization function is proposed and further analyzed.The multi-objective optimization problem is modeled mathematically.Beam collection efficiency(BCE)is the primary factor,followed by the thermal management capability.Some tapers,designed to solve the conflict between BCE and the thermal problem,are reviewed.In addition to these two factors,rectenna design complexity is included as a functional factor in the optimization objective.Weight coefficients are assigned to these factors to prioritize them.Radiating planar arrays with different aperture illumination fields are studied,and their performances are compared using the multi-objective optimization function.Transmitting array size,rectifying array size,transmission distance,and transmitted power remaine constant in various cases,ensuring fair comparisons.The analysis results show that the proposed optimization function is effective in optimizing and selecting the MPT system architecture.It is also noted that the multi-objective optimization function can be expanded to include other factors in the future.展开更多
The multi-objective optimization of backfill effect based on response surface methodology and desirability function(RSM-DF)was conducted.Firstly,the test results show that the uniaxial compressive strength(UCS)increas...The multi-objective optimization of backfill effect based on response surface methodology and desirability function(RSM-DF)was conducted.Firstly,the test results show that the uniaxial compressive strength(UCS)increases with cement sand ratio(CSR),slurry concentration(SC),and curing age(CA),while flow resistance(FR)increases with SC and backfill flow rate(BFR),and decreases with CSR.Then the regression models of UCS and FR as response values were established through RSM.Multi-factor interaction found that CSR-CA impacted UCS most,while SC-BFR impacted FR most.By introducing the desirability function,the optimal backfill parameters were obtained based on RSM-DF(CSR is 1:6.25,SC is 69%,CA is 11.5 d,and BFR is 90 m^(3)/h),showing close results of Design Expert and high reliability for optimization.For a copper mine in China,RSM-DF optimization will reduce cement consumption by 4758 t per year,increase tailings consumption by about 6700 t,and reduce CO_(2)emission by about 4758 t.Thus,RSM-DF provides a new approach for backfill parameters optimization,which has important theoretical and practical values.展开更多
To better meet the needs of crop growth and achieve energy savings and efficiency enhancements,constructing a reliable environmental model to optimize greenhouse decision parameters is an important problem to be solve...To better meet the needs of crop growth and achieve energy savings and efficiency enhancements,constructing a reliable environmental model to optimize greenhouse decision parameters is an important problem to be solved.In this work,a radial-basis function(RBF)neural network was used to mine the potential changes of a greenhouse environment,a temperature error model was established,a multi-objective optimization function of energy consumption was constructed and the corresponding decision parameters were optimized by using a non-dominated sorting genetic algorithm with an elite strategy(NSGA-Ⅱ).The simulation results showed that RBF could clarify the nonlinear relationship among the greenhouse environment variables and decision parameters and the greenhouse temperature.The NSGA-Ⅱcould well search for the Pareto solution for the objective functions.The experimental results showed that after 40 min of combined control of sunshades and sprays,the temperature was reduced from 31℃to 25℃,and the power consumption was 0.5 MJ.Compared with tire three days of July 24,July 25 and July 26,2017,the energy consumption of the controlled production greenhouse was reduced by 37.5%,9.1%and 28.5%,respectively.展开更多
In this paper, we present an algorithm to solve the inequality constrained multi-objective programming (MP) by using a penalty function with objective parameters and constraint penalty parameter. First, the penalty fu...In this paper, we present an algorithm to solve the inequality constrained multi-objective programming (MP) by using a penalty function with objective parameters and constraint penalty parameter. First, the penalty function with objective parameters and constraint penalty parameter for MP and the corresponding unconstraint penalty optimization problem (UPOP) is defined. Under some conditions, a Pareto efficient solution (or a weakly-efficient solution) to UPOP is proved to be a Pareto efficient solution (or a weakly-efficient solution) to MP. The penalty function is proved to be exact under a stable condition. Then, we design an algorithm to solve MP and prove its convergence. Finally, numerical examples show that the algorithm may help decision makers to find a satisfactory solution to MP.展开更多
This paper deals with the optimality conditions and dual theory of multi-objective programming problems involving generalized convexity. New classes of generalized type-I functions are introduced for arcwise connected...This paper deals with the optimality conditions and dual theory of multi-objective programming problems involving generalized convexity. New classes of generalized type-I functions are introduced for arcwise connected functions, and examples are given to show the existence of these functions. By utilizing the new concepts, several sufficient optimality conditions and Mond-Weir type duality results are proposed for non-differentiable multi-objective programming problem.展开更多
The 6-DOF manipulator provides a new option for traditional shipbuilding for its advantages of vast working space,low power consumption,and excellent flexibility.However,the rotation of the end effector along the tool...The 6-DOF manipulator provides a new option for traditional shipbuilding for its advantages of vast working space,low power consumption,and excellent flexibility.However,the rotation of the end effector along the tool axis is functionally redundant when using a robotic arm for five-axis machining.In the process of ship construction,the performance of the parts’protective coating needs to bemachined tomeet the Performance Standard of Protective Coatings(PSPC).The arbitrary redundancy configuration in path planning will result in drastic fluctuations in the robot joint angle,greatly reducing machining quality and efficiency.There have been some studies on singleobjective optimization of redundant variables,However,the quality and efficiency of milling are not affected by a single factor,it is usually influenced by several factors,such as the manipulator stiffness,the joint motion smoothness,and the energy consumption.To solve this problem,this paper proposed a new path optimization method for the industrial robot when it is used for five-axis machining.The path smoothness performance index and the energy consumption index are established based on the joint acceleration and the joint velocity,respectively.The path planning issue is formulated as a constrained multi-objective optimization problem by taking into account the constraints of joint limits and singularity avoidance.Then,the path is split into multiple segments for optimization to avoid the slow convergence rate caused by the high dimension.An algorithm combining the non-dominated sorting genetic algorithm(NSGA-II)and the differential evolution(DE)algorithm is employed to solve the above optimization problem.The simulations validate the effectiveness of the algorithm,showing the improvement of smoothness and the reduction of energy consumption.展开更多
A vague-set-based fuzzy multi-objective decision making model is developed for evaluating bidding plans in a bid- ding purchase process. A group of decision-makers (DMs) first independently assess bidding plans accord...A vague-set-based fuzzy multi-objective decision making model is developed for evaluating bidding plans in a bid- ding purchase process. A group of decision-makers (DMs) first independently assess bidding plans according to their experience and preferences, and these assessments may be expressed as linguistic terms, which are then converted to fuzzy numbers. The resulting decision matrices are then transformed to objective membership grade matrices. The lower bound of satisfaction and upper bound of dissatisfaction are used to determine each bidding plan’s supporting, opposing, and neutral objective sets, which together determine the vague value of a bidding plan. Finally, a score function is employed to rank all bidding plans. A new score function based on vague sets is introduced in the model and a novel method is presented for calculating the lower bound of sat- isfaction and upper bound of dissatisfaction. In a vague-set-based fuzzy multi-objective decision making model, different valua- tions for upper and lower bounds of satisfaction usually lead to distinct ranking results. Therefore, it is crucial to effectively contain DMs’ arbitrariness and subjectivity when these values are determined.展开更多
To assist readers to have a comprehensive understanding, the classical and intelligent methods roundly based on precursory research achievements are summarized in this paper. First, basic conception and description ab...To assist readers to have a comprehensive understanding, the classical and intelligent methods roundly based on precursory research achievements are summarized in this paper. First, basic conception and description about multi-objective (MO) optimization are introduced. Then some definitions and related terminologies are given. Furthermore several MO optimization methods including classical and current intelligent methods are discussed one by one succinctly. Finally evaluations on advantages and disadvantages about these methods are made at the end of the paper.展开更多
Selective logging is well-recognized as an effective practice in sustainable forest management.However,the ecological efficiency or resilience of the residual stand is often in doubt.Recovery time depends on operation...Selective logging is well-recognized as an effective practice in sustainable forest management.However,the ecological efficiency or resilience of the residual stand is often in doubt.Recovery time depends on operational variables,diversity,and forest structure.Selective logging is excellent but is open to changes.This may be resolved by mathematical programming and this study integrates the economic-ecological aspects in multi-objective function by applying two evolutionary algorithms.The function maximizes remaining stand diversity,merchantable logs,and the inverse of distance between trees for harvesting and log landings points.The Brazilian rainforest database(566 trees)was used to simulate our 216-ha model.The log landing design has a maximum volume limit of 500 m3.The nondominated sorting genetic algorithm was applied to solve the main optimization problem.In parallel,a sub-problem(p-facility allocation)was solved for landing allocation by a genetic algorithm.Pareto frontier analysis was applied to distinguish the gradientsα-economic,β-ecological,andγ-equilibrium.As expected,the solutions have high diameter changes in the residual stand(average removal of approximately 16 m^(3) ha^(-1)).All solutions showed a grouping of trees selected for harvesting,although there was no formation of large clearings(percentage of canopy removal<7%,with an average of 2.5 ind ha^(-1)).There were no differences in floristic composition by preferentially selecting species with greater frequency in the initial stand for harvesting.This implies a lower impact on the demographic rates of the remaining stand.The methodology should support projects of reduced impact logging by using spatial-diversity information to guide better practices in tropical forests.展开更多
AIM To define predictors of functional benefit of direct-acting antivirals(DAAs) in patients with chronic hepatitis C virus(HCV) infection and liver cirrhosis.METHODS We analysed a cohort of 199 patients with chronic ...AIM To define predictors of functional benefit of direct-acting antivirals(DAAs) in patients with chronic hepatitis C virus(HCV) infection and liver cirrhosis.METHODS We analysed a cohort of 199 patients with chronic HCV genotype 1, 2, 3 and 4 infection involving previously treated and untreated patients with compensated(76%) and decompensated(24%) liver cirrhosis at two tertiary centres in Germany. Patients were included withtreatment initiation between February 2014 and August 2016. All patients received a combination regimen of one or more DAAs for either 12 or 24 wk. Predictors of functional benefit were assessed in a univariable as well as multivariable model by binary logistic regression analysis.RESULTS Viral clearance was achieved in 88%(175/199) of patients. Sustained virological response(SVR) 12 rates were as follows: among 156 patients with genotype 1 infection the SVR 12 rate was 90%(n = 141); among 7 patients with genotype 2 infection the SVR 12 rate was 57%(n = 4); among 30 patients with genotype 3 infection the SVR 12 rate was 87%(n = 26); and among 6 patients with genotype 4 infection the SVR 12 rate was 67%(n = 4). Follow-up MELD scores were available for 179 patients. A MELD score improvement was observed in 37%(65/179) of patients, no change of MELD score in 41%(74/179) of patients, and an aggravation was observed in 22%(40/179) of patients. We analysed predictors of functional benefit from antiviral therapy in our patients beyond viral eradication. We identified the Child-Pugh score, the MELD score, the number of platelets and the levels of albumin and bilirubin as significant factors for functional benefit.CONCLUSION Our data may contribute to the discussion of potential risks and benefits of antiviral therapy with individual patients infected with HCV and with advanced liver disease.展开更多
The shape and size optimization of brackets in hull structures was conducted to achieve the simultaneous reduction of mass and high stress,where the parametric finite element model was built based on Patran Command La...The shape and size optimization of brackets in hull structures was conducted to achieve the simultaneous reduction of mass and high stress,where the parametric finite element model was built based on Patran Command Language codes.The optimization procedure was executed on Isight platform,on which the linear dimensionless method was introduced to establish the weighted multi-objective function.The extreme processing method was applied and proved effective to normalize the objectives.The bracket was optimized under the typical single loads and design waves,accompanied by the different proportions of weights in the objective function,in which the safety factor function was further established,including yielding,buckling,and fatigue strength,and the weight minimization and safety maximization of the bracket were obtained.The findings of this study illustrate that the dimensionless objectives share equal contributions to the multi-objective function,which enhances the role of weights in the optimization.展开更多
Multi-objective robust state-feedback controller synthesis problems for linear discrete-time uncertain systems are addressed. Based on parameter-dependent Lyapunov functions, the Gl2 and GH2 norm expressed in terms of...Multi-objective robust state-feedback controller synthesis problems for linear discrete-time uncertain systems are addressed. Based on parameter-dependent Lyapunov functions, the Gl2 and GH2 norm expressed in terms of LMI (Linear Matrix Inequality) characterizations are further generalized to cope with the robust analysis for convex polytopic uncertain system. Robust state-feedback controller synthesis conditions are also derived for this class of uncertain systems. Using the above results, multi-objective state-feedback controller synthesis procedures which involve the LMI optimization technique are developed and less conservative than the existing one. An illustrative example verified the validity of the approach.展开更多
Considering research on multi-objective optimization for reliability and performance suffering cost constraints in digital circuits,an improved multi-objective optimization algorithm based on performance and reliabili...Considering research on multi-objective optimization for reliability and performance suffering cost constraints in digital circuits,an improved multi-objective optimization algorithm based on performance and reliability was proposed to solve the problem of discrete system resources configuration in this paper. This algorithm used the particle-swarm optimization( PSO) to evaluate the tradeoffs configuration of the system resources between reliability and performance and proved the feasibility through the simulation.Finally, the information of resources configuration from optimization algorithm was used to effectively guide the system design so as to mitigate soft errors caused by single event effect( SEE).展开更多
Gluten,the protein responsible for the superior viscoelastic properties of refined wheat flour dough over glutenfree cereals,causes celiac disease in people susceptible to gluten-allergy.Moreover,the sustainability of...Gluten,the protein responsible for the superior viscoelastic properties of refined wheat flour dough over glutenfree cereals,causes celiac disease in people susceptible to gluten-allergy.Moreover,the sustainability of using wheat flour in baked foods is threatened by its high cost,especially in countries that depend on imported wheat for their bakery industry.Research has shown that hydrocolloids serve as gluten replacements in baked foods,in response to these challenges.Food hydrocolloids are a class of high-molecular weight polysaccharides and proteins,which serve as functional ingredients in the food industry that modify the foods’rheological and textural properties.They function as stabilizers,viscosity modifiers,gelling agents,water binders,fibres,and inhibitors of ice crystal in foods.Further,food hydrocolloids have also been reported to possess health-promoting properties,such as lowering of postprandial blood glucose and plasma cholesterol concentrations,colon cancer prevention,and modulation of intestinal transit and satiety.They are obtained from plants,animals or microorganisms,and can be used in their natural or modified forms.The aim of this paper is to review the functional benefits of natural and modified hydrocolloids as gluten replacements in baked foods,emphasizing their physicochemical,nutraceutical,and sensorial importance.The application effects of food hydrocolloids as gluten substitutes in gluten-free baked products’quality were discussed.Also,some practical approaches to improve the quality of gluten-free baked products,in response to an increasing consumers’demand and the rising cost of refined wheat flour were highlighted.展开更多
国土空间功能分区是构建可持续开发保护格局、提升资源利用效率的重要途径,但传统方法多侧重功能相似性识别,缺乏对生态、农业、城镇等多类管理目标及成本效益的系统统筹。该研究引入系统保护理念,构建“目标-成本-效益”协同优化的国...国土空间功能分区是构建可持续开发保护格局、提升资源利用效率的重要途径,但传统方法多侧重功能相似性识别,缺乏对生态、农业、城镇等多类管理目标及成本效益的系统统筹。该研究引入系统保护理念,构建“目标-成本-效益”协同优化的国土空间功能分区理论框架,综合运用适宜性评价、景观格局指数分析和分区优化模型(Marxan with Zones),形成由主导功能区与功能混合区构成的分区方法,并在江阴市开展实证研究。结果表明:1)优化分区方案显著提升了自然生态系统的代表性与保护效益,乔木林地、灌木林地等关键生态系统的保护比例提升至30%以上。2)在满足生态保护目标的前提下,农业与城镇功能空间得到适度拓展,基本农田和城镇开发规模较现状有所增加,单位面积成本增幅保持在10%以内,体现出较强的综合效益。3)优化方案在空间结构上呈现较高的集聚性与协调性,集约化农区聚集度由71.21提升至88.5,通过功能混合区在严格保护区与城镇建设区之间构建了有效的过渡带,缓解了潜在的空间利用冲突。研究可为高冲突区域优化国土空间格局和完善主体功能区制度提供方法与实践参考。展开更多
The offshore-onshore integrated energy system (OOIES) comprises offshore gas production platforms,wind farms,and onshore gas-fired combined heat and power plants,facilitating the integrated operation of multiple energ...The offshore-onshore integrated energy system (OOIES) comprises offshore gas production platforms,wind farms,and onshore gas-fired combined heat and power plants,facilitating the integrated operation of multiple energy sources.To address the challenge of optimally configuring the device capacities in carbon capture and power to gas (CC-P2G) amid stochastic fluctuations in offshore gas and wind power outputs,this study proposes a multi-objective approximate dynamic programming algorithm.This algorithm solves the multi-objective stochastic optimal configuration for the device capacities in CC-P2G in OOIES by simultaneously optimizing investment and operation costs,wind power curtailment,and carbon emissions.By leveraging value function matrices for multiple objectives to solve the extended Bellman equation,the multi-objective multi-period model is decomposed into a series of multi-objective single-period optimization problems,which are solved recursively.Additionally,a weighted Chebyshev function is introduced to obtain the compromise optimal solution for multi-objective optimization model during each period.A case study of an OOIES confirms the effectiveness and efficiency of the proposed algorithm.展开更多
基金Project(51074051)supported by the National Natural Science Foundation of ChinaProject(N110307001)supported by the Fundamental Research Funds for the Central Universities,China
文摘In terms of tandem cold mill productivity and product quality, a multi-objective optimization model of rolling schedule based on cost fimction was proposed to determine the stand reductions, inter-stand tensions and rolling speeds for a specified product. The proposed schedule optimization model consists of several single cost fi.mctions, which take rolling force, motor power, inter-stand tension and stand reduction into consideration. The cost function, which can evaluate how far the rolling parameters are from the ideal values, was minimized using the Nelder-Mead simplex method. The proposed rolling schedule optimization method has been applied successfully to the 5-stand tandem cold mill in Tangsteel, and the results from a case study show that the proposed method is superior to those based on empirical formulae.
文摘In the last decade,space solar power satellites(SSPSs)have been conceived to support net-zero carbon emissions and have attracted considerable attention.Electric energy is transmitted to the ground via a microwave power beam,a technology known as microwave power transmission(MPT).Due to the vast transmission distance of tens of thousands of kilometers,the power transmitting antenna array must span up to 1 kilometer in diameter.At the same time,the size of the rectifying array on the ground should extend over a few kilometers.This makes the MPT system of SSPSs significantly larger than the existing aerospace engineering system.To design and operate a rational MPT system,comprehensive optimization is required.Taking the space MPT system engineering into consideration,a novel multi-objective optimization function is proposed and further analyzed.The multi-objective optimization problem is modeled mathematically.Beam collection efficiency(BCE)is the primary factor,followed by the thermal management capability.Some tapers,designed to solve the conflict between BCE and the thermal problem,are reviewed.In addition to these two factors,rectenna design complexity is included as a functional factor in the optimization objective.Weight coefficients are assigned to these factors to prioritize them.Radiating planar arrays with different aperture illumination fields are studied,and their performances are compared using the multi-objective optimization function.Transmitting array size,rectifying array size,transmission distance,and transmitted power remaine constant in various cases,ensuring fair comparisons.The analysis results show that the proposed optimization function is effective in optimizing and selecting the MPT system architecture.It is also noted that the multi-objective optimization function can be expanded to include other factors in the future.
基金Funded by the Deep Underground National Science&Technology Major Project gram of China(No.2024ZD1003704)the National Natural Science Foundation of China(Nos.51834001 and 52374111)。
文摘The multi-objective optimization of backfill effect based on response surface methodology and desirability function(RSM-DF)was conducted.Firstly,the test results show that the uniaxial compressive strength(UCS)increases with cement sand ratio(CSR),slurry concentration(SC),and curing age(CA),while flow resistance(FR)increases with SC and backfill flow rate(BFR),and decreases with CSR.Then the regression models of UCS and FR as response values were established through RSM.Multi-factor interaction found that CSR-CA impacted UCS most,while SC-BFR impacted FR most.By introducing the desirability function,the optimal backfill parameters were obtained based on RSM-DF(CSR is 1:6.25,SC is 69%,CA is 11.5 d,and BFR is 90 m^(3)/h),showing close results of Design Expert and high reliability for optimization.For a copper mine in China,RSM-DF optimization will reduce cement consumption by 4758 t per year,increase tailings consumption by about 6700 t,and reduce CO_(2)emission by about 4758 t.Thus,RSM-DF provides a new approach for backfill parameters optimization,which has important theoretical and practical values.
基金Supported by the National"Thirteenth Five-year Plan"National Key Program(2016YFD0701301)the Heilongjiang Provincial Achievement Transformation Fund Project(NB08B-011)。
文摘To better meet the needs of crop growth and achieve energy savings and efficiency enhancements,constructing a reliable environmental model to optimize greenhouse decision parameters is an important problem to be solved.In this work,a radial-basis function(RBF)neural network was used to mine the potential changes of a greenhouse environment,a temperature error model was established,a multi-objective optimization function of energy consumption was constructed and the corresponding decision parameters were optimized by using a non-dominated sorting genetic algorithm with an elite strategy(NSGA-Ⅱ).The simulation results showed that RBF could clarify the nonlinear relationship among the greenhouse environment variables and decision parameters and the greenhouse temperature.The NSGA-Ⅱcould well search for the Pareto solution for the objective functions.The experimental results showed that after 40 min of combined control of sunshades and sprays,the temperature was reduced from 31℃to 25℃,and the power consumption was 0.5 MJ.Compared with tire three days of July 24,July 25 and July 26,2017,the energy consumption of the controlled production greenhouse was reduced by 37.5%,9.1%and 28.5%,respectively.
文摘In this paper, we present an algorithm to solve the inequality constrained multi-objective programming (MP) by using a penalty function with objective parameters and constraint penalty parameter. First, the penalty function with objective parameters and constraint penalty parameter for MP and the corresponding unconstraint penalty optimization problem (UPOP) is defined. Under some conditions, a Pareto efficient solution (or a weakly-efficient solution) to UPOP is proved to be a Pareto efficient solution (or a weakly-efficient solution) to MP. The penalty function is proved to be exact under a stable condition. Then, we design an algorithm to solve MP and prove its convergence. Finally, numerical examples show that the algorithm may help decision makers to find a satisfactory solution to MP.
文摘This paper deals with the optimality conditions and dual theory of multi-objective programming problems involving generalized convexity. New classes of generalized type-I functions are introduced for arcwise connected functions, and examples are given to show the existence of these functions. By utilizing the new concepts, several sufficient optimality conditions and Mond-Weir type duality results are proposed for non-differentiable multi-objective programming problem.
文摘The 6-DOF manipulator provides a new option for traditional shipbuilding for its advantages of vast working space,low power consumption,and excellent flexibility.However,the rotation of the end effector along the tool axis is functionally redundant when using a robotic arm for five-axis machining.In the process of ship construction,the performance of the parts’protective coating needs to bemachined tomeet the Performance Standard of Protective Coatings(PSPC).The arbitrary redundancy configuration in path planning will result in drastic fluctuations in the robot joint angle,greatly reducing machining quality and efficiency.There have been some studies on singleobjective optimization of redundant variables,However,the quality and efficiency of milling are not affected by a single factor,it is usually influenced by several factors,such as the manipulator stiffness,the joint motion smoothness,and the energy consumption.To solve this problem,this paper proposed a new path optimization method for the industrial robot when it is used for five-axis machining.The path smoothness performance index and the energy consumption index are established based on the joint acceleration and the joint velocity,respectively.The path planning issue is formulated as a constrained multi-objective optimization problem by taking into account the constraints of joint limits and singularity avoidance.Then,the path is split into multiple segments for optimization to avoid the slow convergence rate caused by the high dimension.An algorithm combining the non-dominated sorting genetic algorithm(NSGA-II)and the differential evolution(DE)algorithm is employed to solve the above optimization problem.The simulations validate the effectiveness of the algorithm,showing the improvement of smoothness and the reduction of energy consumption.
基金Project (No. K81077) supported by the Department of Automation, Xiamen University, China
文摘A vague-set-based fuzzy multi-objective decision making model is developed for evaluating bidding plans in a bid- ding purchase process. A group of decision-makers (DMs) first independently assess bidding plans according to their experience and preferences, and these assessments may be expressed as linguistic terms, which are then converted to fuzzy numbers. The resulting decision matrices are then transformed to objective membership grade matrices. The lower bound of satisfaction and upper bound of dissatisfaction are used to determine each bidding plan’s supporting, opposing, and neutral objective sets, which together determine the vague value of a bidding plan. Finally, a score function is employed to rank all bidding plans. A new score function based on vague sets is introduced in the model and a novel method is presented for calculating the lower bound of sat- isfaction and upper bound of dissatisfaction. In a vague-set-based fuzzy multi-objective decision making model, different valua- tions for upper and lower bounds of satisfaction usually lead to distinct ranking results. Therefore, it is crucial to effectively contain DMs’ arbitrariness and subjectivity when these values are determined.
文摘To assist readers to have a comprehensive understanding, the classical and intelligent methods roundly based on precursory research achievements are summarized in this paper. First, basic conception and description about multi-objective (MO) optimization are introduced. Then some definitions and related terminologies are given. Furthermore several MO optimization methods including classical and current intelligent methods are discussed one by one succinctly. Finally evaluations on advantages and disadvantages about these methods are made at the end of the paper.
基金supported by the Coordenacao de Aperfeicoamento de Pessoal de Nível Superior–Brasil (CAPES)–Finance Code 001the Postgraduate Programme in Forest Engineering of the Federal University of Lavras (PPGEF/UFLA)and Group of Optimization and Planning (GOPLAN/UFLA/LEMAF-Forest Management Research Lab)。
文摘Selective logging is well-recognized as an effective practice in sustainable forest management.However,the ecological efficiency or resilience of the residual stand is often in doubt.Recovery time depends on operational variables,diversity,and forest structure.Selective logging is excellent but is open to changes.This may be resolved by mathematical programming and this study integrates the economic-ecological aspects in multi-objective function by applying two evolutionary algorithms.The function maximizes remaining stand diversity,merchantable logs,and the inverse of distance between trees for harvesting and log landings points.The Brazilian rainforest database(566 trees)was used to simulate our 216-ha model.The log landing design has a maximum volume limit of 500 m3.The nondominated sorting genetic algorithm was applied to solve the main optimization problem.In parallel,a sub-problem(p-facility allocation)was solved for landing allocation by a genetic algorithm.Pareto frontier analysis was applied to distinguish the gradientsα-economic,β-ecological,andγ-equilibrium.As expected,the solutions have high diameter changes in the residual stand(average removal of approximately 16 m^(3) ha^(-1)).All solutions showed a grouping of trees selected for harvesting,although there was no formation of large clearings(percentage of canopy removal<7%,with an average of 2.5 ind ha^(-1)).There were no differences in floristic composition by preferentially selecting species with greater frequency in the initial stand for harvesting.This implies a lower impact on the demographic rates of the remaining stand.The methodology should support projects of reduced impact logging by using spatial-diversity information to guide better practices in tropical forests.
文摘AIM To define predictors of functional benefit of direct-acting antivirals(DAAs) in patients with chronic hepatitis C virus(HCV) infection and liver cirrhosis.METHODS We analysed a cohort of 199 patients with chronic HCV genotype 1, 2, 3 and 4 infection involving previously treated and untreated patients with compensated(76%) and decompensated(24%) liver cirrhosis at two tertiary centres in Germany. Patients were included withtreatment initiation between February 2014 and August 2016. All patients received a combination regimen of one or more DAAs for either 12 or 24 wk. Predictors of functional benefit were assessed in a univariable as well as multivariable model by binary logistic regression analysis.RESULTS Viral clearance was achieved in 88%(175/199) of patients. Sustained virological response(SVR) 12 rates were as follows: among 156 patients with genotype 1 infection the SVR 12 rate was 90%(n = 141); among 7 patients with genotype 2 infection the SVR 12 rate was 57%(n = 4); among 30 patients with genotype 3 infection the SVR 12 rate was 87%(n = 26); and among 6 patients with genotype 4 infection the SVR 12 rate was 67%(n = 4). Follow-up MELD scores were available for 179 patients. A MELD score improvement was observed in 37%(65/179) of patients, no change of MELD score in 41%(74/179) of patients, and an aggravation was observed in 22%(40/179) of patients. We analysed predictors of functional benefit from antiviral therapy in our patients beyond viral eradication. We identified the Child-Pugh score, the MELD score, the number of platelets and the levels of albumin and bilirubin as significant factors for functional benefit.CONCLUSION Our data may contribute to the discussion of potential risks and benefits of antiviral therapy with individual patients infected with HCV and with advanced liver disease.
基金This work was financially supported by the Key Research and Development Project of Shandong Province(Grant No.2020CXGC010702).
文摘The shape and size optimization of brackets in hull structures was conducted to achieve the simultaneous reduction of mass and high stress,where the parametric finite element model was built based on Patran Command Language codes.The optimization procedure was executed on Isight platform,on which the linear dimensionless method was introduced to establish the weighted multi-objective function.The extreme processing method was applied and proved effective to normalize the objectives.The bracket was optimized under the typical single loads and design waves,accompanied by the different proportions of weights in the objective function,in which the safety factor function was further established,including yielding,buckling,and fatigue strength,and the weight minimization and safety maximization of the bracket were obtained.The findings of this study illustrate that the dimensionless objectives share equal contributions to the multi-objective function,which enhances the role of weights in the optimization.
基金Project (No. 60374028) supported by the National Natural ScienceFoundation of China
文摘Multi-objective robust state-feedback controller synthesis problems for linear discrete-time uncertain systems are addressed. Based on parameter-dependent Lyapunov functions, the Gl2 and GH2 norm expressed in terms of LMI (Linear Matrix Inequality) characterizations are further generalized to cope with the robust analysis for convex polytopic uncertain system. Robust state-feedback controller synthesis conditions are also derived for this class of uncertain systems. Using the above results, multi-objective state-feedback controller synthesis procedures which involve the LMI optimization technique are developed and less conservative than the existing one. An illustrative example verified the validity of the approach.
文摘Considering research on multi-objective optimization for reliability and performance suffering cost constraints in digital circuits,an improved multi-objective optimization algorithm based on performance and reliability was proposed to solve the problem of discrete system resources configuration in this paper. This algorithm used the particle-swarm optimization( PSO) to evaluate the tradeoffs configuration of the system resources between reliability and performance and proved the feasibility through the simulation.Finally, the information of resources configuration from optimization algorithm was used to effectively guide the system design so as to mitigate soft errors caused by single event effect( SEE).
文摘Gluten,the protein responsible for the superior viscoelastic properties of refined wheat flour dough over glutenfree cereals,causes celiac disease in people susceptible to gluten-allergy.Moreover,the sustainability of using wheat flour in baked foods is threatened by its high cost,especially in countries that depend on imported wheat for their bakery industry.Research has shown that hydrocolloids serve as gluten replacements in baked foods,in response to these challenges.Food hydrocolloids are a class of high-molecular weight polysaccharides and proteins,which serve as functional ingredients in the food industry that modify the foods’rheological and textural properties.They function as stabilizers,viscosity modifiers,gelling agents,water binders,fibres,and inhibitors of ice crystal in foods.Further,food hydrocolloids have also been reported to possess health-promoting properties,such as lowering of postprandial blood glucose and plasma cholesterol concentrations,colon cancer prevention,and modulation of intestinal transit and satiety.They are obtained from plants,animals or microorganisms,and can be used in their natural or modified forms.The aim of this paper is to review the functional benefits of natural and modified hydrocolloids as gluten replacements in baked foods,emphasizing their physicochemical,nutraceutical,and sensorial importance.The application effects of food hydrocolloids as gluten substitutes in gluten-free baked products’quality were discussed.Also,some practical approaches to improve the quality of gluten-free baked products,in response to an increasing consumers’demand and the rising cost of refined wheat flour were highlighted.
文摘国土空间功能分区是构建可持续开发保护格局、提升资源利用效率的重要途径,但传统方法多侧重功能相似性识别,缺乏对生态、农业、城镇等多类管理目标及成本效益的系统统筹。该研究引入系统保护理念,构建“目标-成本-效益”协同优化的国土空间功能分区理论框架,综合运用适宜性评价、景观格局指数分析和分区优化模型(Marxan with Zones),形成由主导功能区与功能混合区构成的分区方法,并在江阴市开展实证研究。结果表明:1)优化分区方案显著提升了自然生态系统的代表性与保护效益,乔木林地、灌木林地等关键生态系统的保护比例提升至30%以上。2)在满足生态保护目标的前提下,农业与城镇功能空间得到适度拓展,基本农田和城镇开发规模较现状有所增加,单位面积成本增幅保持在10%以内,体现出较强的综合效益。3)优化方案在空间结构上呈现较高的集聚性与协调性,集约化农区聚集度由71.21提升至88.5,通过功能混合区在严格保护区与城镇建设区之间构建了有效的过渡带,缓解了潜在的空间利用冲突。研究可为高冲突区域优化国土空间格局和完善主体功能区制度提供方法与实践参考。
基金supported by Guangdong Basic and Applied Basic Research Foundation(No.2023A1515240075)Smart Grid-National Science and Technology Major Project(No.2024ZD0802200).
文摘The offshore-onshore integrated energy system (OOIES) comprises offshore gas production platforms,wind farms,and onshore gas-fired combined heat and power plants,facilitating the integrated operation of multiple energy sources.To address the challenge of optimally configuring the device capacities in carbon capture and power to gas (CC-P2G) amid stochastic fluctuations in offshore gas and wind power outputs,this study proposes a multi-objective approximate dynamic programming algorithm.This algorithm solves the multi-objective stochastic optimal configuration for the device capacities in CC-P2G in OOIES by simultaneously optimizing investment and operation costs,wind power curtailment,and carbon emissions.By leveraging value function matrices for multiple objectives to solve the extended Bellman equation,the multi-objective multi-period model is decomposed into a series of multi-objective single-period optimization problems,which are solved recursively.Additionally,a weighted Chebyshev function is introduced to obtain the compromise optimal solution for multi-objective optimization model during each period.A case study of an OOIES confirms the effectiveness and efficiency of the proposed algorithm.
