Abstract
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) obtains 100 best known values out of 109 public instances, among these 89 instances get their best known values with 100% success rate. By comparing with the well-known related algorithms, computational results demonstrate the effectiveness, efficiency and robustness of the proposed algorithm.
摘要
汽车排序问题涉及混流装配线上由多种车型组成的一个加工序列, 一个混合算法用以搜索违约数最小的序列。 该混合算法以禁忌搜索和大邻域搜索为算法框架, 结合了两个组件以提高算法性能。 一个是平行构建启发式方法, 构建一系列初解用于选择高质量的解, 另一个是小邻域搜索, 进一步改进新解的质量。 计算结果显示, 针对 109 个问题的公共测试集, 该算法得到 100 个已知最好解, 89 个问题得到最好解的成功率是 100%。 结果表明, 与知名相关算法比较, 该算法具有有效性、 高效率和鲁棒性。
Similar content being viewed by others
References
KIS T. On the complexity of the car sequencing problem [J]. Operations Research Letters, 2004, 32(4): 331–335.
GENT I P, WALSH T. CSPLib: a benchmark library for constraints [C]//Proceedings of the Principles and Practice of Constraint Programming. Berlin, Germany: Springer Berlin Heidelberg, 1999: 480–481.
GOTTLIEB J, PUCHTA M, SOLNON C. A study of greedy, local search, and ant colony optimization approaches for car sequencing problems [C]//Applications of Evolutionary Computing. Berlin, Germany: Springer Berlin Heidelberg, 2003: 246–257.
FLIEDNER M, BOYSEN N. Solving the car sequencing problem via Branch & Bound [J]. European Journal of Operational Research, 2008, 191(3): 1023–1042.
ARTIGUES C, HEBRARD E, MAYER-EICHBERGER V, et al. SAT and hybrid models of the car sequencing problem [C]//AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems. Cham, Switzerland: Springer International Publishing, 2014: 268–283.
GOLLE U, ROTHLAUF F, BOYSEN N. Iterative beam search for car sequencing [J]. Annals of Operations Research, 2015, 226(1): 239–254.
ZHANG Xiang-yang, GAO Liang, WEN Long, HUANG Zhao-dong. Parallel construction heuristic combined with constraint propagation for the car sequencing problem [J]. Chinese Journal of Mechanical Engineering, 2017, 30(2): 373–384.
SIALA M, HEBRARD E, HUGUET M J. A study of constraint programming heuristics for the car-sequencing problem [J]. Engineering Applications of Artificial Intelligence, 2015, 38: 34–44.
BAUTISTA J, PEREIRA J, ADENSO-DÍAZ B. A GRASP approach for the extended car sequencing problem [J]. Journal of Scheduling, 2007, 11(1): 3–16.
SOLNON C, CUNG V D, NGUYEN A, et al. The car sequencing problem: Overview of state-of-the-art methods and industrial case-study of the ROADEF’2005 challenge problem [J]. European Journal of Operational Research, 2008, 191(3): 912–927.
CORDEAU J F, LAPORTE G, PASIN F. Iterated tabu search for the car sequencing problem [J]. European Journal of Operational Research, 2008, 191(3): 945–956.
BRIANT O, NADDEF D, MOUNIÉ G. Greedy approach and multi-criteria simulated annealing for the car sequencing problem [J]. European Journal of Operational Research, 2008, 191(3): 993–1003.
GAO Gui-bin, ZHANG Guo-jun, HUANG Gang, et al. Solving material distribution routing problem in mixed manufacturing systems with a hybrid multi-objective evolutionary algorithm [J]. Journal of Central South University, 2012, 19(2): 433–442.
PERRON L, SHAW P, FURNON V. Propagation guided large neighborhood search [C]//Principles and Practice of Constraint Programming. Berlin, Germany: Springer Berlin Heidelberg, 2004: 468–481.
GRAVEL M, GAGNÉ C, PRICE W. Review and comparison of three methods for the solution of the car sequencing problem [J]. Journal of the Operational Research Society, 2005, 56(11): 1287–1295.
PRANDTSTETTER M, RAIDL G R. An integer linear programming approach and a hybrid variable neighborhood search for the car sequencing problem [J]. European Journal of Operational Research, 2008, 191(3): 1004–1022.
ZINFLOU A, GAGNÉ C, GRAVEL M. Genetic algorithm with hybrid integer linear programming crossover operators for the car-sequencing problem [J]. INFOR: Information Systems and Operational Research, 2010, 48(1): 23–37.
THIRUVADY D R, MEYER B, ERNST A. Car sequencing with constraint-based ACO [C]//Proceedings of the 13th Annual Conference on Genetic and Evolutionary Computation, ACM. 2011: 163–170.
THIRUVADY D, ERNST A, WALLACE M. A Lagrangian-ACO matheuristic for car sequencing [J]. EURO Journal on Computational Optimization, 2014, 2(4): 279–296.
DREXL A, KIMMS A. Sequencing JIT mixed-model assembly lines under station-load and part-usage constraints [J]. Management Science, 2001, 47(3): 480–491.
SHAW P. Using constraint programming and local search methods to solve vehicle routing problems [C]//Principles and Practice of Constraint Programming. Berlin, Germany: Springer Berlin Heidelberg, 1998: 417–431.
PISINGER D, ROPKE S. Large neighborhood search [M]//Handbook of metaheuristics. Springer US, 2010: 399–419.
PRUD’HOMME C, LORCA X, JUSSIEN N. Explanationbased large neighborhood search [J]. Constraints, 2014, 19(4): 339–379.
DEMIR E, BEKTAŞ T, LAPORTE G. An adaptive large neighborhood search heuristic for the Pollution-Routing Problem [J]. European Journal of Operational Research, 2012, 223(2): 346–359.
BLUM C, RAIDL G R. Hybridization based on large neighborhood search [M]//Hybrid Metaheuristics. Cham, Switzerland: Springer International Publishing, 2016: 63–82.
GAVRANOVIĆ H. Local search and suffix tree for car-sequencing problem with colors[J]. European Journal of Operational Research, 2008, 191(3): 972–980.
ZUFFEREY N. Tabu search approaches for two car sequencing problems with smoothing constraints metaheuristics for production systems [M]. Cham, Switzerland: Springer International Publishing. 2016: 167–190.
RANGASWAMY B, JAIN A S, GLOVER F. Tabu search candidate list strategies in scheduling [C]//Advances in Computational and Stochastic Optimization, Logic Programming, and Heuristic Search: Interfaces in Computer Science and Operations Research. Kluwer Academic Publishers, 1998: 215–233.
Author information
Authors and Affiliations
Corresponding author
Additional information
Foundation item: Project(51435009) supported by the National Natural Science Foundation of China; Project(LQ14E080002) supported by the Zhejiang Provincial Natural Science Foundation of China; Project supported by the K. C. Wong Magna Fund in Ningbo University, China
Rights and permissions
About this article
Cite this article
Zhang, Xy., Gao, L., Wen, L. et al. A hybrid algorithm based on tabu search and large neighbourhood search for car sequencing problem. J. Cent. South Univ. 25, 315–330 (2018). https://doi.org/10.1007/s11771-018-3739-2
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11771-018-3739-2