Exact and heuristic algorithms for the Travelling Salesman Problem with Multiple Time Windows and Hotel Selection

被引:19
作者
Baltz, Andreas [1 ]
El Ouali, Mourad [1 ]
Jager, Gerold [2 ]
Sauerland, Volkmar [1 ]
Srivastav, Anand [1 ]
机构
[1] Univ Kiel, D-24118 Kiel, Germany
[2] Umea Univ, Umea, Sweden
关键词
tour planning; Travelling Salesman Problem; Travelling Salesman Problem with Multiple Time Windows; Travelling Salesman Problem with Hotel Selection; MODELS;
D O I
10.1057/jors.2014.17
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
We introduce and study the Travelling Salesman Problem with Multiple Time Windows and Hotel Selection (TSP-MTWHS), which generalises the well-known Travelling Salesman Problem with Time Windows and the recently introduced Travelling Salesman Problem with Hotel Selection. The TSP-MTWHS consists in determining a route for a salesman (eg, an employee of a services company) who visits various customers at different locations and different time windows. The salesman may require a several-day tour during which he may need to stay in hotels. The goal is to minimise the tour costs consisting of wage, hotel costs, travelling expenses and penalty fees for possibly omitted customers. We present a mixed integer linear programming (MILP) model for this practical problem and a heuristic combining cheapest insert, 2-OPT and randomised restarting. We show on random instances and on real world instances from industry that the MlLP model can be solved to optimality in reasonable time with a standard MILP solver for several small instances. We also show that the heuristic gives the same solutions for most of the small instances, and is also fast, efficient and practical for large instances.
引用
收藏
页码:615 / 626
页数:12
相关论文
共 21 条
[1]  
[Anonymous], 2024, P INT SCI CONFERENCE
[2]  
Applegate D.L., 2021, TRAVELING SALESMAN P
[3]  
Ascheuer N, 2000, NETWORKS, V36, P69, DOI 10.1002/1097-0037(200009)36:2<69::AID-NET1>3.0.CO
[4]  
2-Q
[5]   Solving the Asymmetric Travelling Salesman Problem with time windows by branch-and-cut [J].
Ascheuer, N ;
Fischetti, M ;
Grötschel, M .
MATHEMATICAL PROGRAMMING, 2001, 90 (03) :475-506
[6]   Branch-and-price: Column generation for solving huge integer programs [J].
Barnhart, C ;
Johnson, EL ;
Nemhauser, GL ;
Savelsbergh, MWP ;
Vance, PH .
OPERATIONS RESEARCH, 1998, 46 (03) :316-329
[7]   The multiple traveling salesman problem: an overview of formulations and solution procedures [J].
Bektas, T .
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE, 2006, 34 (03) :209-219
[8]   Cut-and-solve: An iterative search strategy for combinatorial optimization problems [J].
Climer, Sharlee ;
Zhang, Weixiong .
ARTIFICIAL INTELLIGENCE, 2006, 170 (8-9) :714-738
[9]   A unified tabu search heuristic for vehicle routing problems with time windows [J].
Cordeau, JF ;
Laporte, G ;
Mercier, A .
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY, 2001, 52 (08) :928-936
[10]  
Gomes CP, 1998, FIFTEENTH NATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE (AAAI-98) AND TENTH CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICAL INTELLIGENCE (IAAI-98) - PROCEEDINGS, P431