The evaluation of the minimum distance of linear block codes remains an open problem in coding theory, and it is not easy to determine its true value by classical methods, for this reason the problem has been solved i...The evaluation of the minimum distance of linear block codes remains an open problem in coding theory, and it is not easy to determine its true value by classical methods, for this reason the problem has been solved in the literature with heuristic techniques such as genetic algorithms and local search algorithms. In this paper we propose two approaches to attack the hardness of this problem. The first approach is based on genetic algorithms and it yield to good results comparing to another work based also on genetic algorithms. The second approach is based on a new randomized algorithm which we call 'Multiple Impulse Method (MIM)', where the principle is to search codewords locally around the all-zero codeword perturbed by a minimum level of noise, anticipating that the resultant nearest nonzero codewords will most likely contain the minimum Hamming-weight codeword whose Hamming weight is equal to the minimum distance of the linear code.展开更多
In the paper we discuss and compare two commonly used methods of finding the shortest paths in networks,namely Dijkstra’s and A*algorithms.We compare their effectiveness in terms of traversing road network in circums...In the paper we discuss and compare two commonly used methods of finding the shortest paths in networks,namely Dijkstra’s and A*algorithms.We compare their effectiveness in terms of traversing road network in circumstances that require swift decision making in the event of dynamically changing road conditions on the basis of studies conducted for evacuation plans.To build a proper model of such a network,a method of appropriate edge-weighting is introduced,based on empirical data collected by other researchers.Then,we use the basics of the theory of quasimetric spaces to introduce a heuristic to such graphs,which is easy to calculate metric.The heuristic we obtain is both admissible and consistent,which allows us to use it efficiently in A*search algorithms.The developed application can be used in studies into evacuation from hazardous areas.In this case,optimum calculative efficiency is achievable with a simultaneous reduction of calculation time(when compared to Dijkstra’s algorithm).Our application can be applied during the first stage,i.e.,prior to the occurrence of a disaster,since this is an appropriate time for preparation by planning,drilling,early warning,and designating the rescue services that are to participate in the following stages.展开更多
Airport disruptions often pose challenges in assigning aircraft to gates,resulting in infeasible planned schedules.In particular,a large number of transfer passengers miss their connections in the context of disruptio...Airport disruptions often pose challenges in assigning aircraft to gates,resulting in infeasible planned schedules.In particular,a large number of transfer passengers miss their connections in the context of disruptions,which cause huge economic losses to airlines and serious passengers’dissatisfaction.This paper proposes a set-partitioning-based model to optimize Aircraft-Gate Reassignment with Transfer Passenger Connections(AGRP-TPC),which incorporates flexible gate-swap and aircraft-delay operations to mitigate the overall impact of disruptions.To efficiently solve the model,we introduce the concepts of additive-transfer and nonstop-transfer to handle passenger connections,and develop a Hierarchical Column-and-Row Generation(HCRG)approach guided by airport terminal space attribute.The column generation and row generation procedures solve iteratively until no new variables and constraints are generated.In addition,a follow-on strategy and a diving heuristic are designed to efficiently obtain high-quality solutions.We evaluate the proposed approach using various instances from a major Chinese international airport.Computational results demonstrate that our approach outperforms the comparison algorithms and produces good solutions within the time limit.Detailed results indicate that our approach effectively reduces overall losses in aircraft-gate reassignment following disruptions,and it can serve as an auxiliary decision-making tool for airport operators and airlines.展开更多
In this work,forward current voltage characteristics for multi-quantum wells Al_(0.33)Ga_(0.67)As Schottky diode were measured at temperature ranges from 100 to 300 K.The main parameters of this Schottky diode,such as...In this work,forward current voltage characteristics for multi-quantum wells Al_(0.33)Ga_(0.67)As Schottky diode were measured at temperature ranges from 100 to 300 K.The main parameters of this Schottky diode,such as the ideality factor,barrier height,series resistance and saturation current,have been extracted using both analytical and heuristics methods.Differential evolution(DE),particle swarm optimization(PSO)and artificial bee colony(ABC)have been chosen as candidate heuristics algorithms,while Cheung technic was selected as analytical extraction method.The obtained results show clearly the high performance of DE algorithms in terms of parameters accuracy,convergence speed and robustness.展开更多
An efficient method for quality control of Fructus Aurantii Immaturus (FAI),a famous traditional Chinese medicine (TCM) was established. A simple and reliable high-performance liquid chromatography-photodiode array de...An efficient method for quality control of Fructus Aurantii Immaturus (FAI),a famous traditional Chinese medicine (TCM) was established. A simple and reliable high-performance liquid chromatography-photodiode array detector (HPLC-DAD) procedure coupled with chemometric methods was developed for fingerprint analysis,qualitative analysis and quantitative determination of this herb. In qualitative and quantitative analyses,heuristic evolving latent projection (HELP) method was employed to resolve the overlapping peaks of the tested samples. Two bioactive components,namely hesperidin and naringin,are confirmed and determined,together with four flavonoids compounds tentatively identified including two new ones. From fingerprint analysis,the fingerprint data were processed with correlation coefficients for quantitative expression of their similarity and dissimilarity. The developed method based on an integration of chromatographic fingerprint and quantitative analysis is scientific,and the obtained results can be applied to the quality control of herb medicine.展开更多
Satellite launch vehicle lies at the cross-road of multiple challenging technologies and its design and optimization present a typical example of multidisciplinary design and optimization（MDO） process.The complexity...Satellite launch vehicle lies at the cross-road of multiple challenging technologies and its design and optimization present a typical example of multidisciplinary design and optimization（MDO） process.The complexity of problem demands highly effi-cient and effective algorithm that can optimize the design.Hyper heuristic approach（HHA） based on meta-heuristics is applied to the optimization of air launched satellite launch vehicle（ASLV）.A non-learning random function（NLRF） is proposed to con-trol low-level meta-heuristics（LLMHs） that increases certainty of global solution,an essential ingredient required in product conceptual design phase of aerospace systems.Comprehensive empirical study is performed to evaluate the performance advan-tages of proposed approach over popular non-gradient based optimization methods.Design of ASLV encompasses aerodynamics,propulsion,structure,stages layout,mass distribution,and trajectory modules connected by multidisciplinary feasible design approach.This approach formulates explicit system-level goals and then forwards the design optimization process entirely over to optimizer.This distinctive approach for launch vehicle system design relieves engineers from tedious,iterative task and en-ables them to improve their component level models.Mass is an impetus on vehicle performance and cost,and so it is considered as the core of vehicle design process.Therefore,gross launch mass is to be minimized in HHA.展开更多
In cabin-type component alignment, digital measurement technology is usually adopted to provide guidance for assembly. Depending on the system of measurement, the alignment process can be divided into measurement-assi...In cabin-type component alignment, digital measurement technology is usually adopted to provide guidance for assembly. Depending on the system of measurement, the alignment process can be divided into measurement-assisted assembly(MAA) and force-driven assembly. In MAA,relative pose between components is directly measured to guide assembly, while in force-driven assembly, only contact state can be recognized according to measured six-dimensional force and torque(6 D F/T) and the process is completed based on preset assembly strategy. Aiming to improve the efficiency of force-driven cabin-type component alignment, this paper proposed a heuristic alignment method based on multi-source data fusion. In this method, measured 6 D F/T, pose data and geometric information of components are fused to calculate the relative pose between components and guide the movement of pose adjustment platform. Among these data types, pose data and measured 6 D F/T are combined as data set. To collect the data sets needed for data fusion, dynamic gravity compensation method and hybrid motion control method are designed. Then the relative pose calculation method is elaborated, which transforms collected data sets into discrete geometric elements and calculates the relative poses based on the geometric information of components.Finally, experiments are conducted in simulation environment and the results show that the proposed alignment method is feasible and effective.展开更多
The study aims to propose using a universal heuristic evaluation model （UHEM） to improve the functional and physical performance of residential buildings. Since, ＂everyone should be able to enter and use any part o...The study aims to propose using a universal heuristic evaluation model （UHEM） to improve the functional and physical performance of residential buildings. Since, ＂everyone should be able to enter and use any part of the built environment as independently and naturally as possible＂, the old buildings should be revitalized with respect to an inclusive approach. However, research on current design practice showed that there is a lack of systematic evaluation and revitalization methods. Hence, the main objective of the proposed UHEM model is to evaluate existing residential environments and requalify them with respect to an inclusive approach. The study concludes by highlighting the importance of UHEM from two points of view： （i） the importance of a systematic evaluation approach to effectively deal with the challenge of requalifying the residential environments and （ii） the designers＇ key role during the revitalization process.展开更多
This paper studies the solution technique to solve the DRAMA spares allocation optimization problem. DRAMA model is an analytic spare optimization model of a multi-item, multi-location, and two-echelon inventory syste...This paper studies the solution technique to solve the DRAMA spares allocation optimization problem. DRAMA model is an analytic spare optimization model of a multi-item, multi-location, and two-echelon inventory system. The computation of its system spares availability is much complicated. The objective function and constraint functions of DRAMA model could be written as the separable forms. A new bound heuristic algorithm has been presented by improving the bound heuristic algorithm for solving the reliability redundancy optimization problem (BHA in short). With the results, the proposed algorithm has been found to be more economical and effective than BHA to obtain the solutions of large DRAMA model. The new algorithm could be used to solve reliability redundancy optimization problems with the separable forms.展开更多
There is an old saying,“Give a man a fish,and he will eat for a day.Teach a man to fish,and he will eat for the rest of his life.”In clinical teaching,students should not only be taught about diseases,but their inte...There is an old saying,“Give a man a fish,and he will eat for a day.Teach a man to fish,and he will eat for the rest of his life.”In clinical teaching,students should not only be taught about diseases,but their intelligence should also be cultivated,along with their analytical,comprehension,and independent learning skills.The ability to solve problems enables students to think independently and acquire knowledge.This is known as the heuristic method of teaching.In this study,we mainly analyze the application value of the heuristic method in the clinical teaching of internal medicine.展开更多
A job shop scheduling problem with a combination processing in complex production environment is proposed. Based on the defining of ＂non-elastic combination processing relativity＂ and ＂virtual process＂, the proble...A job shop scheduling problem with a combination processing in complex production environment is proposed. Based on the defining of ＂non-elastic combination processing relativity＂ and ＂virtual process＂, the problem can be simplified and transformed to a traditional one. On the basis of the dispatching rules select engine and considered factors of complex production environment, a heuristic method is designed. The algorithm has been applied to a mould enterprise in Shenzhen for half a year. The practice showed that by using the method suggested the number of delayed orders was decreased about 20% and the productivity was increased by 10 to 20%.展开更多
This study examines the multicriteria scheduling problem on a single machine to minimize three criteria: the maximum cost function, denoted by maximum late work (V<sub>max</sub>), maximum tardy job, denote...This study examines the multicriteria scheduling problem on a single machine to minimize three criteria: the maximum cost function, denoted by maximum late work (V<sub>max</sub>), maximum tardy job, denoted by (T<sub>max</sub>), and maximum earliness (E<sub>max</sub>). We propose several algorithms based on types of objectives function to be optimized when dealing with simultaneous minimization problems with and without weight and hierarchical minimization problems. The proposed Algorithm (3) is to find the set of efficient solutions for 1//F (V<sub>max</sub>, T<sub>max</sub>, E<sub>max</sub>) and 1//(V<sub>max</sub> + T<sub>max</sub> + E<sub>max</sub>). The Local Search Heuristic Methods (Descent Method (DM), Simulated Annealing (SA), Genetic Algorithm (GA), and the Tree Type Heuristics Method (TTHM) are applied to solve all suggested problems. Finally, the experimental results of Algorithm (3) are compared with the results of the Branch and Bound (BAB) method for optimal and Pareto optimal solutions for smaller instance sizes and compared to the Local Search Heuristic Methods for large instance sizes. These results ensure the efficiency of Algorithm (3) in a reasonable time.展开更多
An approach to identifying fuzzy models considering both interpretability and precision was proposed. Firstly, interpretability issues about fuzzy models were analyzed. Then, a heuristic strategy was used to select in...An approach to identifying fuzzy models considering both interpretability and precision was proposed. Firstly, interpretability issues about fuzzy models were analyzed. Then, a heuristic strategy was used to select input variables by increasing the number of input variables, and the Gustafson-Kessel fuzzy clustering algorithm, combined with the least square method, was used to identify the fuzzy model. Subsequently, an interpretability measure was described by the product of the number of input variables and the number of rules, while precision was weighted by root mean square error, and the selection objective function concerning interpretability and precision was defined. Given the maximum and minimum number of input variables and rules, a set of fuzzy models was constructed. Finally, the optimal fuzzy model was selected by the objective function, and was optimized by a genetic algorithm to achieve a good tradeoff between interpretability and precision. The performance of the proposed method was illustrated by the well-known Box-Jenkins gas furnace benchmark; the results demonstrate its validity.展开更多
To overcome the problem that soft sensor models cannot be updated with the process changes, a soft sensor modeling algorithm based on hybrid fuzzy c-means （FCM） algorithm and incremental support vector machines （I...To overcome the problem that soft sensor models cannot be updated with the process changes, a soft sensor modeling algorithm based on hybrid fuzzy c-means （FCM） algorithm and incremental support vector machines （ISVM） is proposed. This hybrid algorithm FCMISVM includes three parts： samples clustering based on FCM algorithm, learning algorithm based on ISVM, and heuristic sample displacement method. In the training process, the training samples are first clustered by the FCM algorithm, and then by training each clustering with the SVM algorithm, a sub-model is built to each clustering. In the predicting process, when an incremental sample that represents new operation information is introduced in the model, the fuzzy membership function of the sample to each clustering is first computed by the FCM algorithm. Then, a corresponding SVM sub-model of the clustering with the largest fuzzy membership function is used to predict and perform incremental learning so the model can be updated on-line. An old sample chosen by heuristic sample displacement method is then discarded from the sub-model to control the size of the working set. The proposed method is applied to predict the p-xylene （PX） purity in the adsorption separation process. Simulation results indicate that the proposed method actually increases the model＇s adaptive abilities to various operation conditions and improves its generalization capability.展开更多
Turkey is highly prone to landslides because of the geological and geographic location.The study area,which is located in a tectonically active region,has been significantly affected by mass movements.Flow type landsl...Turkey is highly prone to landslides because of the geological and geographic location.The study area,which is located in a tectonically active region,has been significantly affected by mass movements.Flow type landslides are frequently observed due to this location.This study aims at determining the source area and propagation of debris flows in the study area.We used the heuristic method to extract source areas of debris flow,and then used receiver operating characteristic(ROC)curve analysis to assess the performance of the method,and finally calculated the Area under curve(AUC)values being 83.64%and 80.39%for the success rate and prediction rate,respectively.We calculated potential propagation area and runout distance with Flow-R software.In conclusion,the obtained results(susceptibility map,propagation and runout distance)are very important for decisionmakers at the region located on an active fault zone,which is highly prone to natural disasters.The outputs of this study could be used in site selection studies,designing erosion prevention systems and protecting existing human-made structures.展开更多
We extended an improved version of the discrete particle swarm optimization (DPSO) algorithm proposed by Liao et al.(2007) to solve the dynamic facility layout problem (DFLP). A computational study was performed with ...We extended an improved version of the discrete particle swarm optimization (DPSO) algorithm proposed by Liao et al.(2007) to solve the dynamic facility layout problem (DFLP). A computational study was performed with the existing heuristic algorithms, including the dynamic programming (DP), genetic algorithm (GA), simulated annealing (SA), hybrid ant system (HAS), hybrid simulated annealing (SA-EG), hybrid genetic algorithms (NLGA and CONGA). The proposed DPSO algorithm, SA, HAS, GA, DP, SA-EG, NLGA, and CONGA obtained the best solutions for 33, 24, 20, 10, 12, 20, 5, and 2 of the 48 problems from (Balakrishnan and Cheng, 2000), respectively. These results show that the DPSO is very effective in dealing with the DFLP. The extended DPSO also has very good computational efficiency when the problem size increases.展开更多
This paper addresses the scheduling and inventory management of a straight pipeline system connecting a single refinery to multiple distribution centers.By increasing the number of batches and time periods,maintaining...This paper addresses the scheduling and inventory management of a straight pipeline system connecting a single refinery to multiple distribution centers.By increasing the number of batches and time periods,maintaining the model resolution by using linear programming-based methods and commercial solvers would be very time-consuming.In this paper,we make an attempt to utilize the problem structure and develop a decomposition-based algorithm capable of finding near-optimal solutions for large instances in a reasonable time.The algorithm starts with a relaxed version of the model and adds a family of cuts on the fly,so that a near-optimal solution is obtained within a few iterations.The idea behind the cut generation is based on the knowledge of the underlying problem structure.Computational experiments on a real-world data case and some randomly generated instances confirm the efficiency of the proposed algorithm in terms of the solution quality and time.展开更多
Airlines adjust their flight schedules to satisfy more stringent airport capacity constraints caused by inclement weather or other unexpected disruptions.The problem will be more important and complicated if uncertain...Airlines adjust their flight schedules to satisfy more stringent airport capacity constraints caused by inclement weather or other unexpected disruptions.The problem will be more important and complicated if uncertain disruptions occur in hub airports.A two-stage stochastic programming model was established to deal with the realtime flight schedule recovery and passenger re-accommodation problem.The first-stage model represents the flight re-timing and re-fleeting decision in current time period when capacity information is deterministic,while the second-stage recourse model evaluates the passenger delay given the first-stage solutions when one future scenario is realized.Aiming at the large size of the problem and requirement for quick response,an algorithmic framework combining the sample average approximation and heuristic method was proposed.The computational results indicated of that the proposed method could obtain solutions with around 5% optimal gaps,and the computing time was linearly positive to the sample size.展开更多
A quantitative structure-retention relationship（QSRR） study has been carried out on the gas chromatograph-mass spectrometry（GC-MS） system retention time（RT） of two sets of illicit drugs by using molecular struct...A quantitative structure-retention relationship（QSRR） study has been carried out on the gas chromatograph-mass spectrometry（GC-MS） system retention time（RT） of two sets of illicit drugs by using molecular structural descriptors.Heuristic method（HM） was utilized to construct the linear models.Appropriate models with low standard errors and high correlation coefficients were obtained（R2=0.9873,F=390.18 for data set 1 and R2=0.9881,F=749.13 for data set 2）.The results of leave-one-out cross validation showed good predictive ability of these proposed models（R c2v= 0.9812 and R c2v= 0.9824,respectively）.Each molecular descriptor in the two models was disputed to unfold the relationship between the molecular structures and RT.展开更多
The traditional approach to solvent selction in the extractive distillation process strictly focuses on the change in the relative voltility of light-heavy components induced by the solvent.However,the total annual co...The traditional approach to solvent selction in the extractive distillation process strictly focuses on the change in the relative voltility of light-heavy components induced by the solvent.However,the total annual cost of the process may not be minimal when the solvent induces the largest change in relative volatility.This work presents a heuristic method for selecting the optimal solvent to minimize the total annual cost.The functional relationship between the relative volatility and the total annual cost is established,where the main factors,such as the relative volatility of the light-heavy components and the relative volatility of the heavy-component solvent,are taken into account.Binary azeotropic mixtures of methanol-toluene and methanol-acetone are separated to verify the feasibility of the model.The results show that using the solvent with the minimal two-column extractive distillation index,the process achieves a minimal total annual cost.The method is conducive for sustainable advancements in chemistry and engineering because a suitable solvent can be selected without simulation verification.展开更多
文摘The evaluation of the minimum distance of linear block codes remains an open problem in coding theory, and it is not easy to determine its true value by classical methods, for this reason the problem has been solved in the literature with heuristic techniques such as genetic algorithms and local search algorithms. In this paper we propose two approaches to attack the hardness of this problem. The first approach is based on genetic algorithms and it yield to good results comparing to another work based also on genetic algorithms. The second approach is based on a new randomized algorithm which we call 'Multiple Impulse Method (MIM)', where the principle is to search codewords locally around the all-zero codeword perturbed by a minimum level of noise, anticipating that the resultant nearest nonzero codewords will most likely contain the minimum Hamming-weight codeword whose Hamming weight is equal to the minimum distance of the linear code.
基金the National Science Centre in Poland,grant number 2018/29/B/HS4/01020o-funded under the framework of the subsidy for tertiary education,aimed at academies and universities which participated in the IDUB Contest(“Inicjatywa Doskona?o sci-Uczelnia Badawcza”)。
文摘In the paper we discuss and compare two commonly used methods of finding the shortest paths in networks,namely Dijkstra’s and A*algorithms.We compare their effectiveness in terms of traversing road network in circumstances that require swift decision making in the event of dynamically changing road conditions on the basis of studies conducted for evacuation plans.To build a proper model of such a network,a method of appropriate edge-weighting is introduced,based on empirical data collected by other researchers.Then,we use the basics of the theory of quasimetric spaces to introduce a heuristic to such graphs,which is easy to calculate metric.The heuristic we obtain is both admissible and consistent,which allows us to use it efficiently in A*search algorithms.The developed application can be used in studies into evacuation from hazardous areas.In this case,optimum calculative efficiency is achievable with a simultaneous reduction of calculation time(when compared to Dijkstra’s algorithm).Our application can be applied during the first stage,i.e.,prior to the occurrence of a disaster,since this is an appropriate time for preparation by planning,drilling,early warning,and designating the rescue services that are to participate in the following stages.
基金supported by the National Natural Science Foundation of China(No.U2333218).
文摘Airport disruptions often pose challenges in assigning aircraft to gates,resulting in infeasible planned schedules.In particular,a large number of transfer passengers miss their connections in the context of disruptions,which cause huge economic losses to airlines and serious passengers’dissatisfaction.This paper proposes a set-partitioning-based model to optimize Aircraft-Gate Reassignment with Transfer Passenger Connections(AGRP-TPC),which incorporates flexible gate-swap and aircraft-delay operations to mitigate the overall impact of disruptions.To efficiently solve the model,we introduce the concepts of additive-transfer and nonstop-transfer to handle passenger connections,and develop a Hierarchical Column-and-Row Generation(HCRG)approach guided by airport terminal space attribute.The column generation and row generation procedures solve iteratively until no new variables and constraints are generated.In addition,a follow-on strategy and a diving heuristic are designed to efficiently obtain high-quality solutions.We evaluate the proposed approach using various instances from a major Chinese international airport.Computational results demonstrate that our approach outperforms the comparison algorithms and produces good solutions within the time limit.Detailed results indicate that our approach effectively reduces overall losses in aircraft-gate reassignment following disruptions,and it can serve as an auxiliary decision-making tool for airport operators and airlines.
文摘In this work,forward current voltage characteristics for multi-quantum wells Al_(0.33)Ga_(0.67)As Schottky diode were measured at temperature ranges from 100 to 300 K.The main parameters of this Schottky diode,such as the ideality factor,barrier height,series resistance and saturation current,have been extracted using both analytical and heuristics methods.Differential evolution(DE),particle swarm optimization(PSO)and artificial bee colony(ABC)have been chosen as candidate heuristics algorithms,while Cheung technic was selected as analytical extraction method.The obtained results show clearly the high performance of DE algorithms in terms of parameters accuracy,convergence speed and robustness.
基金Project(20875104) supported by the National Natural Science Foundation of ChinaProject(10SDF22) supported by the Special Foundation of China Postdoctoral ScienceProject(201021200011) supported by the Advanced Research Plan of Central South University, China
文摘An efficient method for quality control of Fructus Aurantii Immaturus (FAI),a famous traditional Chinese medicine (TCM) was established. A simple and reliable high-performance liquid chromatography-photodiode array detector (HPLC-DAD) procedure coupled with chemometric methods was developed for fingerprint analysis,qualitative analysis and quantitative determination of this herb. In qualitative and quantitative analyses,heuristic evolving latent projection (HELP) method was employed to resolve the overlapping peaks of the tested samples. Two bioactive components,namely hesperidin and naringin,are confirmed and determined,together with four flavonoids compounds tentatively identified including two new ones. From fingerprint analysis,the fingerprint data were processed with correlation coefficients for quantitative expression of their similarity and dissimilarity. The developed method based on an integration of chromatographic fingerprint and quantitative analysis is scientific,and the obtained results can be applied to the quality control of herb medicine.
文摘Satellite launch vehicle lies at the cross-road of multiple challenging technologies and its design and optimization present a typical example of multidisciplinary design and optimization（MDO） process.The complexity of problem demands highly effi-cient and effective algorithm that can optimize the design.Hyper heuristic approach（HHA） based on meta-heuristics is applied to the optimization of air launched satellite launch vehicle（ASLV）.A non-learning random function（NLRF） is proposed to con-trol low-level meta-heuristics（LLMHs） that increases certainty of global solution,an essential ingredient required in product conceptual design phase of aerospace systems.Comprehensive empirical study is performed to evaluate the performance advan-tages of proposed approach over popular non-gradient based optimization methods.Design of ASLV encompasses aerodynamics,propulsion,structure,stages layout,mass distribution,and trajectory modules connected by multidisciplinary feasible design approach.This approach formulates explicit system-level goals and then forwards the design optimization process entirely over to optimizer.This distinctive approach for launch vehicle system design relieves engineers from tedious,iterative task and en-ables them to improve their component level models.Mass is an impetus on vehicle performance and cost,and so it is considered as the core of vehicle design process.Therefore,gross launch mass is to be minimized in HHA.
基金co-supported by the Special Research on Civil Aircraft of China (No.MJZ-2017-J-96)the Defense Industrial Technology Development Program of China (No.JCKY2016206B009)。
文摘In cabin-type component alignment, digital measurement technology is usually adopted to provide guidance for assembly. Depending on the system of measurement, the alignment process can be divided into measurement-assisted assembly(MAA) and force-driven assembly. In MAA,relative pose between components is directly measured to guide assembly, while in force-driven assembly, only contact state can be recognized according to measured six-dimensional force and torque(6 D F/T) and the process is completed based on preset assembly strategy. Aiming to improve the efficiency of force-driven cabin-type component alignment, this paper proposed a heuristic alignment method based on multi-source data fusion. In this method, measured 6 D F/T, pose data and geometric information of components are fused to calculate the relative pose between components and guide the movement of pose adjustment platform. Among these data types, pose data and measured 6 D F/T are combined as data set. To collect the data sets needed for data fusion, dynamic gravity compensation method and hybrid motion control method are designed. Then the relative pose calculation method is elaborated, which transforms collected data sets into discrete geometric elements and calculates the relative poses based on the geometric information of components.Finally, experiments are conducted in simulation environment and the results show that the proposed alignment method is feasible and effective.
文摘The study aims to propose using a universal heuristic evaluation model （UHEM） to improve the functional and physical performance of residential buildings. Since, ＂everyone should be able to enter and use any part of the built environment as independently and naturally as possible＂, the old buildings should be revitalized with respect to an inclusive approach. However, research on current design practice showed that there is a lack of systematic evaluation and revitalization methods. Hence, the main objective of the proposed UHEM model is to evaluate existing residential environments and requalify them with respect to an inclusive approach. The study concludes by highlighting the importance of UHEM from two points of view： （i） the importance of a systematic evaluation approach to effectively deal with the challenge of requalifying the residential environments and （ii） the designers＇ key role during the revitalization process.
文摘This paper studies the solution technique to solve the DRAMA spares allocation optimization problem. DRAMA model is an analytic spare optimization model of a multi-item, multi-location, and two-echelon inventory system. The computation of its system spares availability is much complicated. The objective function and constraint functions of DRAMA model could be written as the separable forms. A new bound heuristic algorithm has been presented by improving the bound heuristic algorithm for solving the reliability redundancy optimization problem (BHA in short). With the results, the proposed algorithm has been found to be more economical and effective than BHA to obtain the solutions of large DRAMA model. The new algorithm could be used to solve reliability redundancy optimization problems with the separable forms.
文摘There is an old saying,“Give a man a fish,and he will eat for a day.Teach a man to fish,and he will eat for the rest of his life.”In clinical teaching,students should not only be taught about diseases,but their intelligence should also be cultivated,along with their analytical,comprehension,and independent learning skills.The ability to solve problems enables students to think independently and acquire knowledge.This is known as the heuristic method of teaching.In this study,we mainly analyze the application value of the heuristic method in the clinical teaching of internal medicine.
基金Supported by Research Fund for the Doctoral Program of Higher Education of China(20060487072)National Key Technology R&D Program(2006BAF01A43)
文摘A job shop scheduling problem with a combination processing in complex production environment is proposed. Based on the defining of ＂non-elastic combination processing relativity＂ and ＂virtual process＂, the problem can be simplified and transformed to a traditional one. On the basis of the dispatching rules select engine and considered factors of complex production environment, a heuristic method is designed. The algorithm has been applied to a mould enterprise in Shenzhen for half a year. The practice showed that by using the method suggested the number of delayed orders was decreased about 20% and the productivity was increased by 10 to 20%.
文摘This study examines the multicriteria scheduling problem on a single machine to minimize three criteria: the maximum cost function, denoted by maximum late work (V<sub>max</sub>), maximum tardy job, denoted by (T<sub>max</sub>), and maximum earliness (E<sub>max</sub>). We propose several algorithms based on types of objectives function to be optimized when dealing with simultaneous minimization problems with and without weight and hierarchical minimization problems. The proposed Algorithm (3) is to find the set of efficient solutions for 1//F (V<sub>max</sub>, T<sub>max</sub>, E<sub>max</sub>) and 1//(V<sub>max</sub> + T<sub>max</sub> + E<sub>max</sub>). The Local Search Heuristic Methods (Descent Method (DM), Simulated Annealing (SA), Genetic Algorithm (GA), and the Tree Type Heuristics Method (TTHM) are applied to solve all suggested problems. Finally, the experimental results of Algorithm (3) are compared with the results of the Branch and Bound (BAB) method for optimal and Pareto optimal solutions for smaller instance sizes and compared to the Local Search Heuristic Methods for large instance sizes. These results ensure the efficiency of Algorithm (3) in a reasonable time.
文摘An approach to identifying fuzzy models considering both interpretability and precision was proposed. Firstly, interpretability issues about fuzzy models were analyzed. Then, a heuristic strategy was used to select input variables by increasing the number of input variables, and the Gustafson-Kessel fuzzy clustering algorithm, combined with the least square method, was used to identify the fuzzy model. Subsequently, an interpretability measure was described by the product of the number of input variables and the number of rules, while precision was weighted by root mean square error, and the selection objective function concerning interpretability and precision was defined. Given the maximum and minimum number of input variables and rules, a set of fuzzy models was constructed. Finally, the optimal fuzzy model was selected by the objective function, and was optimized by a genetic algorithm to achieve a good tradeoff between interpretability and precision. The performance of the proposed method was illustrated by the well-known Box-Jenkins gas furnace benchmark; the results demonstrate its validity.
基金Supported by the National Natural Science Foundation of China （60421002） and priority supported financially by ＂the New Century 151 Talent Project＂ of Zhejiang Province.
文摘To overcome the problem that soft sensor models cannot be updated with the process changes, a soft sensor modeling algorithm based on hybrid fuzzy c-means （FCM） algorithm and incremental support vector machines （ISVM） is proposed. This hybrid algorithm FCMISVM includes three parts： samples clustering based on FCM algorithm, learning algorithm based on ISVM, and heuristic sample displacement method. In the training process, the training samples are first clustered by the FCM algorithm, and then by training each clustering with the SVM algorithm, a sub-model is built to each clustering. In the predicting process, when an incremental sample that represents new operation information is introduced in the model, the fuzzy membership function of the sample to each clustering is first computed by the FCM algorithm. Then, a corresponding SVM sub-model of the clustering with the largest fuzzy membership function is used to predict and perform incremental learning so the model can be updated on-line. An old sample chosen by heuristic sample displacement method is then discarded from the sub-model to control the size of the working set. The proposed method is applied to predict the p-xylene （PX） purity in the adsorption separation process. Simulation results indicate that the proposed method actually increases the model＇s adaptive abilities to various operation conditions and improves its generalization capability.
文摘Turkey is highly prone to landslides because of the geological and geographic location.The study area,which is located in a tectonically active region,has been significantly affected by mass movements.Flow type landslides are frequently observed due to this location.This study aims at determining the source area and propagation of debris flows in the study area.We used the heuristic method to extract source areas of debris flow,and then used receiver operating characteristic(ROC)curve analysis to assess the performance of the method,and finally calculated the Area under curve(AUC)values being 83.64%and 80.39%for the success rate and prediction rate,respectively.We calculated potential propagation area and runout distance with Flow-R software.In conclusion,the obtained results(susceptibility map,propagation and runout distance)are very important for decisionmakers at the region located on an active fault zone,which is highly prone to natural disasters.The outputs of this study could be used in site selection studies,designing erosion prevention systems and protecting existing human-made structures.
文摘We extended an improved version of the discrete particle swarm optimization (DPSO) algorithm proposed by Liao et al.(2007) to solve the dynamic facility layout problem (DFLP). A computational study was performed with the existing heuristic algorithms, including the dynamic programming (DP), genetic algorithm (GA), simulated annealing (SA), hybrid ant system (HAS), hybrid simulated annealing (SA-EG), hybrid genetic algorithms (NLGA and CONGA). The proposed DPSO algorithm, SA, HAS, GA, DP, SA-EG, NLGA, and CONGA obtained the best solutions for 33, 24, 20, 10, 12, 20, 5, and 2 of the 48 problems from (Balakrishnan and Cheng, 2000), respectively. These results show that the DPSO is very effective in dealing with the DFLP. The extended DPSO also has very good computational efficiency when the problem size increases.
文摘This paper addresses the scheduling and inventory management of a straight pipeline system connecting a single refinery to multiple distribution centers.By increasing the number of batches and time periods,maintaining the model resolution by using linear programming-based methods and commercial solvers would be very time-consuming.In this paper,we make an attempt to utilize the problem structure and develop a decomposition-based algorithm capable of finding near-optimal solutions for large instances in a reasonable time.The algorithm starts with a relaxed version of the model and adds a family of cuts on the fly,so that a near-optimal solution is obtained within a few iterations.The idea behind the cut generation is based on the knowledge of the underlying problem structure.Computational experiments on a real-world data case and some randomly generated instances confirm the efficiency of the proposed algorithm in terms of the solution quality and time.
基金supported by the National Natural Science Foundation of China(Nos.61079014,71171111)the Funding of Outstanding Doctoral Dissertation in Nanjing University of Aeronautics and Astronautics(No.BCXJ1314)the Funding of Jiangsu Innovation Program for Graduate Education(No.CXZZ13_0174)
文摘Airlines adjust their flight schedules to satisfy more stringent airport capacity constraints caused by inclement weather or other unexpected disruptions.The problem will be more important and complicated if uncertain disruptions occur in hub airports.A two-stage stochastic programming model was established to deal with the realtime flight schedule recovery and passenger re-accommodation problem.The first-stage model represents the flight re-timing and re-fleeting decision in current time period when capacity information is deterministic,while the second-stage recourse model evaluates the passenger delay given the first-stage solutions when one future scenario is realized.Aiming at the large size of the problem and requirement for quick response,an algorithmic framework combining the sample average approximation and heuristic method was proposed.The computational results indicated of that the proposed method could obtain solutions with around 5% optimal gaps,and the computing time was linearly positive to the sample size.
基金supported by the key program of National Natural Science Foundation of China (No. 90612016)
文摘A quantitative structure-retention relationship（QSRR） study has been carried out on the gas chromatograph-mass spectrometry（GC-MS） system retention time（RT） of two sets of illicit drugs by using molecular structural descriptors.Heuristic method（HM） was utilized to construct the linear models.Appropriate models with low standard errors and high correlation coefficients were obtained（R2=0.9873,F=390.18 for data set 1 and R2=0.9881,F=749.13 for data set 2）.The results of leave-one-out cross validation showed good predictive ability of these proposed models（R c2v= 0.9812 and R c2v= 0.9824,respectively）.Each molecular descriptor in the two models was disputed to unfold the relationship between the molecular structures and RT.
基金This work is supported by the National Natural Science Foundation of China(Grant Nos.21776145 and 21676152).
文摘The traditional approach to solvent selction in the extractive distillation process strictly focuses on the change in the relative voltility of light-heavy components induced by the solvent.However,the total annual cost of the process may not be minimal when the solvent induces the largest change in relative volatility.This work presents a heuristic method for selecting the optimal solvent to minimize the total annual cost.The functional relationship between the relative volatility and the total annual cost is established,where the main factors,such as the relative volatility of the light-heavy components and the relative volatility of the heavy-component solvent,are taken into account.Binary azeotropic mixtures of methanol-toluene and methanol-acetone are separated to verify the feasibility of the model.The results show that using the solvent with the minimal two-column extractive distillation index,the process achieves a minimal total annual cost.The method is conducive for sustainable advancements in chemistry and engineering because a suitable solvent can be selected without simulation verification.
