Multi-objective optimization of crashworthiness in automobile front-end structure was performed,and finite element model(FEM)was validated by experimental results to ensure that FEM can predict the response value with...Multi-objective optimization of crashworthiness in automobile front-end structure was performed,and finite element model(FEM)was validated by experimental results to ensure that FEM can predict the response value with sufficient accuracy.Seven design variables and four crashworthiness indicators were defined.Through orthogonal design method,18 FEMs were established,and the response values of crashworthiness indicators were extracted.By using the variable-response specimen matrix,Kriging surrogate model(KSM)was constructed to replace FEM to refect the function correlation between variables and responses.The accuracy of KSM was also validated.Finally,the simulated annealing optimization algorithm was implemented in KSM to seek optimal and reliable solutions.Based on the optimal results and comparison analysis,the 9096-th iteration point was the optimal solution.Although the intrusion of firewall and the mass of optimal structure increased slightly,the vehicle acceleration of the optimal solution decreased by 6.9%,which fectively reduced the risk of occupant injury.展开更多
As two independent problems,scheduling for parts fabrication line and sequencing for mixed-model assembly line have been addressed respectively by many researchers.However,these two problems should be considered simul...As two independent problems,scheduling for parts fabrication line and sequencing for mixed-model assembly line have been addressed respectively by many researchers.However,these two problems should be considered simultaneously to improve the efficiency of the whole fabrication/assembly systems.By far,little research effort is devoted to sequencing problems for mixed-model fabrication/assembly systems.This paper is concerned about the sequencing problems in pull production systems which are composed of one mixed-model assembly line with limited intermediate buffers and two flexible parts fabrication flow lines with identical parallel machines and limited intermediate buffers.Two objectives are considered simultaneously：minimizing the total variation in parts consumption in the assembly line and minimizing the total makespan cost in the fabrication/assembly system.The integrated optimization framework,mathematical models and the method to construct the complete schedules for the fabrication lines according to the production sequences for the first stage in fabrication lines are presented.Since the above problems are non-deterministic polynomial-hard（NP-hard）,a modified multi-objective genetic algorithm is proposed for solving the models,in which a method to generate the production sequences for the fabrication lines from the production sequences for the assembly line and a method to generate the initial population are put forward,new selection,crossover and mutation operators are designed,and Pareto ranking method and sharing function method are employed to evaluate the individuals＇ fitness.The feasibility and efficiency of the multi-objective genetic algorithm is shown by computational comparison with a multi-objective simulated annealing algorithm.The sequencing problems for mixed-model production systems can be solved effectively by the proposed modified multi-objective genetic algorithm.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
On the basis of computational of transonic viscid flow, the simulated annealing algorithm, used in statistical mechanics to study solid cooling process, is adaptedfor soving multi-objective cascades design problem. Th...On the basis of computational of transonic viscid flow, the simulated annealing algorithm, used in statistical mechanics to study solid cooling process, is adaptedfor soving multi-objective cascades design problem. The simulated annealing algorithmdraws an analogy between the energy minimization in physical system and the objectivefunction in the real design problem, To model the multi-objective functions, a minimumdeviation method is used. In this paper, the loss and work are considered as the objectivefunctions. Simulated results indicate that this algorithm can be effectively applied to theimprovement of the design for transonic turbine cascades.展开更多
This paper describes one approach to the design of reinforced concrete (RC) bridge piers, using a three-hybrid multi- objective simulated annealing (SA) algorithm with a neighborhood move based on the mutation operato...This paper describes one approach to the design of reinforced concrete (RC) bridge piers, using a three-hybrid multi- objective simulated annealing (SA) algorithm with a neighborhood move based on the mutation operator from the genetic algorithms (GAs), namely MOSAMO1, MOSAMO2 and MOSAMO3. The procedure is applied to three objective functions: the economic cost, the reinforcing steel congestion and the embedded CO 2 emissions. Additional results for a random walk and a descent local search multi-objective algorithm are presented. The evaluation of solutions follows the Spanish Code for structural concrete. The methodology was applied to a typical bridge pier of 23.97 m in height. This example involved 110 design variables. Results indicate that algorithm MOSAMO2 outperforms other algorithms regarding the definition of Pareto fronts. Further, the proposed procedure will help structural engineers to enhance their bridge pier designs.展开更多
To improve the efficiency of gate reassignment and optimize the plan of gate reassignment,the concept of disruption management is introduced,and a multi-objective programming model for airport gate reassignment is pro...To improve the efficiency of gate reassignment and optimize the plan of gate reassignment,the concept of disruption management is introduced,and a multi-objective programming model for airport gate reassignment is proposed.Considering the interests of passengers and the airport,the model minimizes the total flight delay,the total passengers′walking distance and the number of flights reassigned to other gates different from the planned ones.According to the characteristics of the gate reassignment,the model is simplified.As the multi-objective programming model is hard to reach the optimal solutions simultaneously,a threshold of satisfactory solutions of the model is set.Then a simulated annealing algorithm is designed for the model.Case studies show that the model decreases the total flight delay to the satisfactory solutions,and minimizes the total passengers′walking distance.The least change of planned assignment is also reached.The results achieve the goals of disruption management.Therefore,the model is verified to be effective.展开更多
Purpose–Flexible job-shop scheduling is significant for different manufacturing industries nowadays.Moreover,consideration of transportation time during scheduling makes it more practical and useful.The purpose of th...Purpose–Flexible job-shop scheduling is significant for different manufacturing industries nowadays.Moreover,consideration of transportation time during scheduling makes it more practical and useful.The purpose of this paper is to investigate multi-objective flexible job-shop scheduling problem(MOFJSP)considering transportation time.Design/methodology/approach–A hybrid genetic algorithm(GA)approach is integrated with simulated annealing to solve the MOFJSP considering transportation time,and an external elitism memory library is employed as a knowledge library to direct GA search into the region of better performance.Findings–The performance of the proposed algorithm is tested on different MOFJSP taken from literature.Experimental results show that proposed algorithm performs better than the original GA in terms of quality of solution and distribution of the solution,especially when the number of jobs and the flexibility of the machine increase.Originality/value–Most of existing studies have not considered the transportation time during scheduling of jobs.The transportation time is significantly desired to be included in the FJSP when the time of transportation of jobs has significant impact on the completion time of jobs.Meanwhile,GA is one of primary algorithms extensively used to address MOFJSP in literature.However,to solve the MOFJSP,the original GA has a possibility to get a premature convergence and it has a slow convergence speed.To overcome these problems,a new hybrid GA is developed in this paper.展开更多
Background:Laser scanning and individual-tree detection are used increasingly in forest inventories.As a consequence,methods that optimize forest management at the level of individual trees will be gradually developed...Background:Laser scanning and individual-tree detection are used increasingly in forest inventories.As a consequence,methods that optimize forest management at the level of individual trees will be gradually developed and adopted.Results:The current study proposed a hierarchical two-level optimization method for tree-level planning where the cutting years are optimized at the higher level.The lower-level optimization allocates the trees to the cutting events in an optimal way.The higher-level optimization employed differential evolution whereas the lower-level problem was solved with the simulated annealing metaheuristic.The method was demonstrated with a 30 m30 m sample plot of planted Larix olgensis.The baseline case maximized the net present value as the only management objective.The solution suggested heavy thinning from above and a rotation length of 62 years.The baseline problem was enhanced to mixed stands where species diversity was used as another management objective.The method was also demonstrated in a problem that considered the complexity of stand structure,in addition to net present value.The objective variables that were used to measure complexity were the Shannon index(species diversity),Gini index(tree size diversity),and the index of Clark and Evans,which was used to describe the spatial distribution of trees.The article also presents a method to include natural advance regeneration in the optimization problem and optimize the parameters of simulated annealing simultaneously with the cutting years.Conclusions:The study showed that optimization approaches developed for forest-level planning can be adapted to problems where treatment prescriptions are required for individual trees.展开更多
The paper presents a procedure to design water network. First of all, water reuse system, water regeneration reuse system (including regeneration recycle) and wastewater treatment system are designed separately. But t...The paper presents a procedure to design water network. First of all, water reuse system, water regeneration reuse system (including regeneration recycle) and wastewater treatment system are designed separately. But the interaction between different parts demands that each part is designed iteratively to optimize the whole water network. Therefore, on the basis of the separated design a water netvrork superstructure including reuse, regeneration and wastewater treatment is established from the system engineering point of view. And a multi-objective adaptive simulated annealing genetic algorithm is adopted to simultaneously integrate the overall water netvrork to balance the economic and environmental effects. The algorithm overcomes the defect of local optimum of simulated annealing (SA), avoids the pre-maturation of genetic algorithm (GA) and finds a set of solutions (pareto front) in acceptable computer time. Prom the pareto front, a point with minimum fresh water consumption will be extended to zero discharge as our ultimate goal.展开更多
In the paper, it is discussed that the method on how to transform the multi-person bilevel multi-objective decision making problem into the equivalent generalized multi-objective decision making problem by using Kuhn-...In the paper, it is discussed that the method on how to transform the multi-person bilevel multi-objective decision making problem into the equivalent generalized multi-objective decision making problem by using Kuhn-Tucker sufficient and necessary condition. In order to embody the decision maker′s hope and transform it into single-objective decision making problem with the help of ε-constraint method. Then we can obtain the global optimal solution by means of simulated annealing algorithm.展开更多
In this paper, we propose a multi-criteria machine-schedules decision making method that can be applied to a produc-tion environment involving several unrelated parallel machines and we will focus on three objectives:...In this paper, we propose a multi-criteria machine-schedules decision making method that can be applied to a produc-tion environment involving several unrelated parallel machines and we will focus on three objectives: minimizing makespan, total flow time, and total number of tardy jobs. The decision making method consists of three phases. In the first phase, a mathematical model of a single machine scheduling problem, of which the objective is a weighted sum of the three objectives, is constructed. Such a model will be repeatedly solved by the CPLEX in the proposed Multi-Objective Simulated Annealing (MOSA) algorithm. In the second phase, the MOSA that integrates job clustering method, job group scheduling method, and job group – machine assignment method, is employed to obtain a set of non-dominated group schedules. During this phase, CPLEX software and the bipartite weighted matching algorithm are used repeatedly as parts of the MOSA algorithm. In the last phase, the technique of data envelopment analysis is applied to determine the most preferable schedule. A practical example is then presented in order to demonstrate the applicability of the proposed decision making method.展开更多
Crew rostering system is a daily grind in the management of both corporation and enterprise. A fair and reasonable rostering method plays a very important role in the arousing worker’s enthusiasm and improving the wo...Crew rostering system is a daily grind in the management of both corporation and enterprise. A fair and reasonable rostering method plays a very important role in the arousing worker’s enthusiasm and improving the work efficiency. This paper presents a method of building models for automatic crew rostering mode with computer and advancing the multi-objective optimum scheme. The method to build models for crew rostering system is also discussed. The question to crew rostering system model is solved by genetic algorithms and simulated annealing algorithms. Simulation results show the correctness of algorithms. The actual data of the airways have justified its reasonability and efficiency.展开更多
文摘Multi-objective optimization of crashworthiness in automobile front-end structure was performed,and finite element model(FEM)was validated by experimental results to ensure that FEM can predict the response value with sufficient accuracy.Seven design variables and four crashworthiness indicators were defined.Through orthogonal design method,18 FEMs were established,and the response values of crashworthiness indicators were extracted.By using the variable-response specimen matrix,Kriging surrogate model(KSM)was constructed to replace FEM to refect the function correlation between variables and responses.The accuracy of KSM was also validated.Finally,the simulated annealing optimization algorithm was implemented in KSM to seek optimal and reliable solutions.Based on the optimal results and comparison analysis,the 9096-th iteration point was the optimal solution.Although the intrusion of firewall and the mass of optimal structure increased slightly,the vehicle acceleration of the optimal solution decreased by 6.9%,which fectively reduced the risk of occupant injury.
基金supported by National Natural Science Foundation of China (Grant No.50875101)National Hi-tech Research and Development Program of China (863 Program,Grant No.2007AA04Z186)
文摘As two independent problems,scheduling for parts fabrication line and sequencing for mixed-model assembly line have been addressed respectively by many researchers.However,these two problems should be considered simultaneously to improve the efficiency of the whole fabrication/assembly systems.By far,little research effort is devoted to sequencing problems for mixed-model fabrication/assembly systems.This paper is concerned about the sequencing problems in pull production systems which are composed of one mixed-model assembly line with limited intermediate buffers and two flexible parts fabrication flow lines with identical parallel machines and limited intermediate buffers.Two objectives are considered simultaneously：minimizing the total variation in parts consumption in the assembly line and minimizing the total makespan cost in the fabrication/assembly system.The integrated optimization framework,mathematical models and the method to construct the complete schedules for the fabrication lines according to the production sequences for the first stage in fabrication lines are presented.Since the above problems are non-deterministic polynomial-hard（NP-hard）,a modified multi-objective genetic algorithm is proposed for solving the models,in which a method to generate the production sequences for the fabrication lines from the production sequences for the assembly line and a method to generate the initial population are put forward,new selection,crossover and mutation operators are designed,and Pareto ranking method and sharing function method are employed to evaluate the individuals＇ fitness.The feasibility and efficiency of the multi-objective genetic algorithm is shown by computational comparison with a multi-objective simulated annealing algorithm.The sequencing problems for mixed-model production systems can be solved effectively by the proposed modified multi-objective genetic algorithm.
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.
文摘On the basis of computational of transonic viscid flow, the simulated annealing algorithm, used in statistical mechanics to study solid cooling process, is adaptedfor soving multi-objective cascades design problem. The simulated annealing algorithmdraws an analogy between the energy minimization in physical system and the objectivefunction in the real design problem, To model the multi-objective functions, a minimumdeviation method is used. In this paper, the loss and work are considered as the objectivefunctions. Simulated results indicate that this algorithm can be effectively applied to theimprovement of the design for transonic turbine cascades.
基金supported by the Spanish Ministry of Science and Innovation(No. BIA2011-23602)the European Community with the European Regional Development Fund (FEDER), Spain
文摘This paper describes one approach to the design of reinforced concrete (RC) bridge piers, using a three-hybrid multi- objective simulated annealing (SA) algorithm with a neighborhood move based on the mutation operator from the genetic algorithms (GAs), namely MOSAMO1, MOSAMO2 and MOSAMO3. The procedure is applied to three objective functions: the economic cost, the reinforcing steel congestion and the embedded CO 2 emissions. Additional results for a random walk and a descent local search multi-objective algorithm are presented. The evaluation of solutions follows the Spanish Code for structural concrete. The methodology was applied to a typical bridge pier of 23.97 m in height. This example involved 110 design variables. Results indicate that algorithm MOSAMO2 outperforms other algorithms regarding the definition of Pareto fronts. Further, the proposed procedure will help structural engineers to enhance their bridge pier designs.
基金Supported by the National Natural Science Foundation of China(71103034)the Natural Science Foundation of Jiangsu Province(bk2011084)
文摘To improve the efficiency of gate reassignment and optimize the plan of gate reassignment,the concept of disruption management is introduced,and a multi-objective programming model for airport gate reassignment is proposed.Considering the interests of passengers and the airport,the model minimizes the total flight delay,the total passengers′walking distance and the number of flights reassigned to other gates different from the planned ones.According to the characteristics of the gate reassignment,the model is simplified.As the multi-objective programming model is hard to reach the optimal solutions simultaneously,a threshold of satisfactory solutions of the model is set.Then a simulated annealing algorithm is designed for the model.Case studies show that the model decreases the total flight delay to the satisfactory solutions,and minimizes the total passengers′walking distance.The least change of planned assignment is also reached.The results achieve the goals of disruption management.Therefore,the model is verified to be effective.
基金supported by National Social Science Foundation of China under the project of 18BGL003.
文摘Purpose–Flexible job-shop scheduling is significant for different manufacturing industries nowadays.Moreover,consideration of transportation time during scheduling makes it more practical and useful.The purpose of this paper is to investigate multi-objective flexible job-shop scheduling problem(MOFJSP)considering transportation time.Design/methodology/approach–A hybrid genetic algorithm(GA)approach is integrated with simulated annealing to solve the MOFJSP considering transportation time,and an external elitism memory library is employed as a knowledge library to direct GA search into the region of better performance.Findings–The performance of the proposed algorithm is tested on different MOFJSP taken from literature.Experimental results show that proposed algorithm performs better than the original GA in terms of quality of solution and distribution of the solution,especially when the number of jobs and the flexibility of the machine increase.Originality/value–Most of existing studies have not considered the transportation time during scheduling of jobs.The transportation time is significantly desired to be included in the FJSP when the time of transportation of jobs has significant impact on the completion time of jobs.Meanwhile,GA is one of primary algorithms extensively used to address MOFJSP in literature.However,to solve the MOFJSP,the original GA has a possibility to get a premature convergence and it has a slow convergence speed.To overcome these problems,a new hybrid GA is developed in this paper.
基金This research was financially supported by the Natural Science Foundation of China(No.U21A20244&No.32071758)the Fundamental Research Funds for the Central Universities of China(No.2572020BA01).
文摘Background:Laser scanning and individual-tree detection are used increasingly in forest inventories.As a consequence,methods that optimize forest management at the level of individual trees will be gradually developed and adopted.Results:The current study proposed a hierarchical two-level optimization method for tree-level planning where the cutting years are optimized at the higher level.The lower-level optimization allocates the trees to the cutting events in an optimal way.The higher-level optimization employed differential evolution whereas the lower-level problem was solved with the simulated annealing metaheuristic.The method was demonstrated with a 30 m30 m sample plot of planted Larix olgensis.The baseline case maximized the net present value as the only management objective.The solution suggested heavy thinning from above and a rotation length of 62 years.The baseline problem was enhanced to mixed stands where species diversity was used as another management objective.The method was also demonstrated in a problem that considered the complexity of stand structure,in addition to net present value.The objective variables that were used to measure complexity were the Shannon index(species diversity),Gini index(tree size diversity),and the index of Clark and Evans,which was used to describe the spatial distribution of trees.The article also presents a method to include natural advance regeneration in the optimization problem and optimize the parameters of simulated annealing simultaneously with the cutting years.Conclusions:The study showed that optimization approaches developed for forest-level planning can be adapted to problems where treatment prescriptions are required for individual trees.
文摘The paper presents a procedure to design water network. First of all, water reuse system, water regeneration reuse system (including regeneration recycle) and wastewater treatment system are designed separately. But the interaction between different parts demands that each part is designed iteratively to optimize the whole water network. Therefore, on the basis of the separated design a water netvrork superstructure including reuse, regeneration and wastewater treatment is established from the system engineering point of view. And a multi-objective adaptive simulated annealing genetic algorithm is adopted to simultaneously integrate the overall water netvrork to balance the economic and environmental effects. The algorithm overcomes the defect of local optimum of simulated annealing (SA), avoids the pre-maturation of genetic algorithm (GA) and finds a set of solutions (pareto front) in acceptable computer time. Prom the pareto front, a point with minimum fresh water consumption will be extended to zero discharge as our ultimate goal.
基金This project is supported by National Natural Science Foundation of China( 6 9874 0 0 9) and theNatural Science Foundation of Heilongjiang Province( A0 0 0 4 )
文摘In the paper, it is discussed that the method on how to transform the multi-person bilevel multi-objective decision making problem into the equivalent generalized multi-objective decision making problem by using Kuhn-Tucker sufficient and necessary condition. In order to embody the decision maker′s hope and transform it into single-objective decision making problem with the help of ε-constraint method. Then we can obtain the global optimal solution by means of simulated annealing algorithm.
文摘In this paper, we propose a multi-criteria machine-schedules decision making method that can be applied to a produc-tion environment involving several unrelated parallel machines and we will focus on three objectives: minimizing makespan, total flow time, and total number of tardy jobs. The decision making method consists of three phases. In the first phase, a mathematical model of a single machine scheduling problem, of which the objective is a weighted sum of the three objectives, is constructed. Such a model will be repeatedly solved by the CPLEX in the proposed Multi-Objective Simulated Annealing (MOSA) algorithm. In the second phase, the MOSA that integrates job clustering method, job group scheduling method, and job group – machine assignment method, is employed to obtain a set of non-dominated group schedules. During this phase, CPLEX software and the bipartite weighted matching algorithm are used repeatedly as parts of the MOSA algorithm. In the last phase, the technique of data envelopment analysis is applied to determine the most preferable schedule. A practical example is then presented in order to demonstrate the applicability of the proposed decision making method.
文摘Crew rostering system is a daily grind in the management of both corporation and enterprise. A fair and reasonable rostering method plays a very important role in the arousing worker’s enthusiasm and improving the work efficiency. This paper presents a method of building models for automatic crew rostering mode with computer and advancing the multi-objective optimum scheme. The method to build models for crew rostering system is also discussed. The question to crew rostering system model is solved by genetic algorithms and simulated annealing algorithms. Simulation results show the correctness of algorithms. The actual data of the airways have justified its reasonability and efficiency.
