Simultaneous dock assignment and sequencing of inbound trucks under a fixed outbound truck schedule in multi-door cross docking operations

被引:85
作者
Liao, T. W. [1 ]
Egbelu, P. J. [2 ]
Chang, P. C. [3 ]
机构
[1] Louisiana State Univ, Dept Construct Management & Ind Engn, Baton Rouge, LA 70803 USA
[2] New Jersey Inst Technol, Sch Management, Newark, NJ 07102 USA
[3] Yuan Ze Univ, Dept Informat Management, Chungli 32003, Taiwan
关键词
Cross docking; Dock assignment; Sequencing; Hybrid metaheuristics; Differential evolution; Ant colony optimization; Tabu search; Simulated annealing; Combinatorial optimization; SUPPLY CHAIN NETWORK; DIFFERENTIAL EVOLUTION; TEMPORARY-STORAGE; TIME WINDOWS; DESIGN; OPTIMIZATION; CROSSDOCKING; HEURISTICS; ALGORITHMS; MAKESPAN;
D O I
10.1016/j.ijpe.2012.03.037
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This paper studies the simultaneous dock assignment and sequencing of inbound trucks for a multi-door cross docking operation with the objective to minimize total weighted tardiness, under a fixed outbound truck departure schedule. The problem is newly formulated and solved by six different metaheuristic algorithms, which include simulated annealing, tabu search, ant colony optimization, differential evolution, and two hybrid differential-evolution algorithms. To evaluate the total weighted tardiness associated with any given inbound-truck sequence and dock assignment, an operational policy is developed. This policy is employed by every metaheuristic algorithm in searching for the optimal dock assignment and sequence. Each metaheuristic algorithm is tested with 40 problems. The major conclusions are: (1) metaheuristic is generally an effective optimization method for the subject problem; (2) population based metaheuristic algorithms are generally more effective than projection based metaheuristic algorithms: (3) proper selection of algorithmic parameters is important and more critical for projection based metaheuristic algorithms than population based algorithms: (4) the two best algorithms are ant colony optimization and hybrid differential evolution 2: among them. ACO takes less time than hybrid 2 and thus can be declared the best among all the six metaheuristic algorithms tested. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码:212 / 229
页数:18
相关论文
共 39 条
[1]   A bounded dynamic programming approach to schedule operations in a cross docking platform [J].
Alpan, Guelguen ;
Larbi, Rim ;
Penz, Bernard .
COMPUTERS & INDUSTRIAL ENGINEERING, 2011, 60 (03) :385-396
[2]  
[Anonymous], 1992, OPTIMIZATION LEARNIN
[3]  
[Anonymous], SCIENCE
[4]  
Apte U.M., 2000, International Journal of Logistics Research and Applications, V3, P291, DOI [10.1080/713682769, DOI 10.1080/713682769]
[5]   Meta-heuristics implementation for scheduling of trucks in a cross-docking system with temporary storage [J].
Arabani, A. R. Boloori ;
Ghomi, S. M. T. Fatemi ;
Zandieh, M. .
EXPERT SYSTEMS WITH APPLICATIONS, 2011, 38 (03) :1964-1979
[6]   The best shape for a crossdock [J].
Bartholdi, JJ ;
Gue, KR .
TRANSPORTATION SCIENCE, 2004, 38 (02) :235-244
[7]   Cross dock scheduling: Classification, literature review and research agenda [J].
Boysen, Nils ;
Fliedner, Malte .
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE, 2010, 38 (06) :413-422
[8]   Scheduling inbound and outbound trucks at cross docking terminals [J].
Boysen, Nils ;
Fliedner, Malte ;
Scholl, Armin .
OR SPECTRUM, 2010, 32 (01) :135-161
[9]   Truck scheduling at zero-inventory cross docking terminals [J].
Boysen, Nils .
COMPUTERS & OPERATIONS RESEARCH, 2010, 37 (01) :32-41
[10]   Minimizing makespan in two-stage hybrid cross docking scheduling problem [J].
Chen, Feng ;
Song, Kailei .
COMPUTERS & OPERATIONS RESEARCH, 2009, 36 (06) :2066-2073