The car sequencing problem(CSP)concerns a production sequence of different types of cars in the mixed-model assembly line.A hybrid algorithm is proposed to find an assembly sequence of CSP with minimum violations.Firs...The car sequencing problem(CSP)concerns a production sequence of different types of cars in the mixed-model assembly line.A hybrid algorithm is proposed to find an assembly sequence of CSP with minimum violations.Firstly,the hybrid algorithm is based on the tabu search and large neighborhood search(TLNS),servicing as the framework.Moreover,two components are incorporated into the hybrid algorithm.One is the parallel constructive heuristic(PCH)that is used to construct a set of initial solutions and find some high quality solutions,and the other is the small neighborhood search(SNS)which is designed to improve the new constructed solutions.The computational results show that the proposed hybrid algorithm(PCH+TLNS+SNS)obtains100best known values out of109public instances,among these89instances get their best known values with100%success rate.By comparing with the well-known related algorithms,computational results demonstrate the effectiveness,efficiency and robustness of the proposed algorithm.展开更多
The material distribution routing problem in the manufacturing system is a complex combinatorial optimization problem and its main task is to deliver materials to the working stations with low cost and high efficiency...The material distribution routing problem in the manufacturing system is a complex combinatorial optimization problem and its main task is to deliver materials to the working stations with low cost and high efficiency. A multi-objective model was presented for the material distribution routing problem in mixed manufacturing systems, and it was solved by a hybrid multi-objective evolutionary algorithm (HMOEA). The characteristics of the HMOEA are as follows: 1) A route pool is employed to preserve the best routes for the population initiation; 2) A specialized best?worst route crossover (BWRC) mode is designed to perform the crossover operators for selecting the best route from Chromosomes 1 to exchange with the worst one in Chromosomes 2, so that the better genes are inherited to the offspring; 3) A route swap mode is used to perform the mutation for improving the convergence speed and preserving the better gene; 4) Local heuristics search methods are applied in this algorithm. Computational study of a practical case shows that the proposed algorithm can decrease the total travel distance by 51.66%, enhance the average vehicle load rate by 37.85%, cut down 15 routes and reduce a deliver vehicle. The convergence speed of HMOEA is faster than that of famous NSGA-II.展开更多
In China, economic centers are far from energy storage bases, so it is significant to select a proper energy transferring mode to improve the efficiency of energy usage. To solve this problem, an optimal allocation mo...In China, economic centers are far from energy storage bases, so it is significant to select a proper energy transferring mode to improve the efficiency of energy usage. To solve this problem, an optimal allocation model based on energy transfer mode was proposed after objective function for optimizing energy using efficiency was established, and then, a new Tabu search and particle swarm hybrid optimizing algorithm was proposed to find solutions. While actual data of energy demand and distribution in China were selected for analysis, the economic critical value in comparison between the long-distance coal transfer and electric power transmission was gained. Based on the above discussion, some proposals were put forward for optimal allocation of energy transfer modes in China. By comparing other three traditional methods that are based on regional price differences, freight rates and annual cost with the proposed method, the result indicates that the economic efficiency of the energy transfer can be enhanced by 3.14%, 5.78% and 6.01%, respectively.展开更多
The problem of minimizing the maximum lateness on a single machine with family setups is considered.To solve the problem, dominance property is studied and then introduced into the tabu search（TS） algorithm.With the...The problem of minimizing the maximum lateness on a single machine with family setups is considered.To solve the problem, dominance property is studied and then introduced into the tabu search（TS） algorithm.With the dominance property, most unpromising neighbors can be excluded from the neighborhood, which makes the search process always focus on the most promising areas of the solution space.The proposed algorithms are tested both on the randomly generated problems and on the real-life problems.Computational results show that the proposed TS algorithm outperforms the best existing algorithm and can solve the real-life problems in about 1.3 on average.展开更多
基金Project(51435009) supported by the National Natural Science Foundation of ChinaProject(LQ14E080002) supported by the Zhejiang Provincial Natural Science Foundation of ChinaProject supported by the K.C.Wong Magna Fund in Ningbo University,China
文摘The car sequencing problem(CSP)concerns a production sequence of different types of cars in the mixed-model assembly line.A hybrid algorithm is proposed to find an assembly sequence of CSP with minimum violations.Firstly,the hybrid algorithm is based on the tabu search and large neighborhood search(TLNS),servicing as the framework.Moreover,two components are incorporated into the hybrid algorithm.One is the parallel constructive heuristic(PCH)that is used to construct a set of initial solutions and find some high quality solutions,and the other is the small neighborhood search(SNS)which is designed to improve the new constructed solutions.The computational results show that the proposed hybrid algorithm(PCH+TLNS+SNS)obtains100best known values out of109public instances,among these89instances get their best known values with100%success rate.By comparing with the well-known related algorithms,computational results demonstrate the effectiveness,efficiency and robustness of the proposed algorithm.
基金Project(50775089)supported by the National Natural Science Foundation of ChinaProject(2007AA04Z190,2009AA043301)supported by the National High Technology Research and Development Program of ChinaProject(2005CB724100)supported by the National Basic Research Program of China
文摘The material distribution routing problem in the manufacturing system is a complex combinatorial optimization problem and its main task is to deliver materials to the working stations with low cost and high efficiency. A multi-objective model was presented for the material distribution routing problem in mixed manufacturing systems, and it was solved by a hybrid multi-objective evolutionary algorithm (HMOEA). The characteristics of the HMOEA are as follows: 1) A route pool is employed to preserve the best routes for the population initiation; 2) A specialized best?worst route crossover (BWRC) mode is designed to perform the crossover operators for selecting the best route from Chromosomes 1 to exchange with the worst one in Chromosomes 2, so that the better genes are inherited to the offspring; 3) A route swap mode is used to perform the mutation for improving the convergence speed and preserving the better gene; 4) Local heuristics search methods are applied in this algorithm. Computational study of a practical case shows that the proposed algorithm can decrease the total travel distance by 51.66%, enhance the average vehicle load rate by 37.85%, cut down 15 routes and reduce a deliver vehicle. The convergence speed of HMOEA is faster than that of famous NSGA-II.
基金Project(20050079008) supported by the Specialized Research Fund for the Doctoral Program of Higher Education
文摘In China, economic centers are far from energy storage bases, so it is significant to select a proper energy transferring mode to improve the efficiency of energy usage. To solve this problem, an optimal allocation model based on energy transfer mode was proposed after objective function for optimizing energy using efficiency was established, and then, a new Tabu search and particle swarm hybrid optimizing algorithm was proposed to find solutions. While actual data of energy demand and distribution in China were selected for analysis, the economic critical value in comparison between the long-distance coal transfer and electric power transmission was gained. Based on the above discussion, some proposals were put forward for optimal allocation of energy transfer modes in China. By comparing other three traditional methods that are based on regional price differences, freight rates and annual cost with the proposed method, the result indicates that the economic efficiency of the energy transfer can be enhanced by 3.14%, 5.78% and 6.01%, respectively.
基金supported by the Major State Basic Research Development Program of China (973 Program)(2002CB312205)the National Natural Science Foundation of China (60574077+2 种基金 60874071 60834004)the National High Technology Research and Development Program of China (863 Program) (2007AA04Z102)
文摘The problem of minimizing the maximum lateness on a single machine with family setups is considered.To solve the problem, dominance property is studied and then introduced into the tabu search（TS） algorithm.With the dominance property, most unpromising neighbors can be excluded from the neighborhood, which makes the search process always focus on the most promising areas of the solution space.The proposed algorithms are tested both on the randomly generated problems and on the real-life problems.Computational results show that the proposed TS algorithm outperforms the best existing algorithm and can solve the real-life problems in about 1.3 on average.
