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 problem of sequential fault diagnosis is to construct a diagnosis tree that can isolate the failure sources with minimal test cost. Pervious sequential fault diagnosis strategy generating algorithms only consider ...The problem of sequential fault diagnosis is to construct a diagnosis tree that can isolate the failure sources with minimal test cost. Pervious sequential fault diagnosis strategy generating algorithms only consider the execution cost at application stage, which may result in a solution with poor quality from the view of life cycle cost. Furthermore, due to the fact that uncertain information exists extensively in the real-world systems, the tests are always imperfect. In order to reduce the cost of fault diagnosis in the realistic systems, the sequential fault diagnosis problem with imperfect tests considering life cycle cost is presented and formulated in this work, which is an intractable NP-hard AND/OR decision tree construction problem. An algorithm based on AND/OR graph search is proposed to solve this problem. Heuristic search based on information theory is applied to generate the sub-tree in the algorithm. Some practical issues such as the method to improve the computational efficiency and the diagnosis strategy with multi-outcome tests are discussed. The algorithm is tested and compared with previous algorithms on the simulated systems with different scales and uncertainty. Application on a wheel momentum system of a spacecraft is studied in detail. Both the simulation and application results suggest that the cost of the diagnosis strategy can be reduced significantly by using the proposed algorithm, especially when the placement cost of the tests constitutes a large part of the total cost.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(C1320063131)supported by China Civil Space Foundation
文摘The problem of sequential fault diagnosis is to construct a diagnosis tree that can isolate the failure sources with minimal test cost. Pervious sequential fault diagnosis strategy generating algorithms only consider the execution cost at application stage, which may result in a solution with poor quality from the view of life cycle cost. Furthermore, due to the fact that uncertain information exists extensively in the real-world systems, the tests are always imperfect. In order to reduce the cost of fault diagnosis in the realistic systems, the sequential fault diagnosis problem with imperfect tests considering life cycle cost is presented and formulated in this work, which is an intractable NP-hard AND/OR decision tree construction problem. An algorithm based on AND/OR graph search is proposed to solve this problem. Heuristic search based on information theory is applied to generate the sub-tree in the algorithm. Some practical issues such as the method to improve the computational efficiency and the diagnosis strategy with multi-outcome tests are discussed. The algorithm is tested and compared with previous algorithms on the simulated systems with different scales and uncertainty. Application on a wheel momentum system of a spacecraft is studied in detail. Both the simulation and application results suggest that the cost of the diagnosis strategy can be reduced significantly by using the proposed algorithm, especially when the placement cost of the tests constitutes a large part of the total cost.
