Declarative Representation and Solution of Vehicle Routing with Pickup and Delivery Problem

被引:6
作者
Badica, Amelia [1 ]
Badica, Costin [1 ]
Leon, Florin [2 ]
Luncean, Lucian [3 ]
机构
[1] Univ Craiova, Craiova, Romania
[2] Univ Gheorghe Asachi Iasi, Iasi, Romania
[3] Romanian German Univ Sibiu, Sibiu, Romania
来源
INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE (ICCS 2017) | 2017年 / 108卷
关键词
constraint logic programming; vehicle routing; pickup and delivery problem;
D O I
10.1016/j.procs.2017.05.261
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Recently we have proposed a multi-agent system that provides an intelligent logistics brokerage service focusing on the transport activity for the efficient allocation of transport resources (vehicles or trucks) to the transport applications. The freight broker agent has a major role to coordinate transportation arrangements of transport customers (usually shippers and consignees) with transport resource providers or carriers, following the freight broker business model. We focus on the fundamental function of this business that aims to find available trucks and to define their feasible routes for transporting requested customer loads. The main contribution of this paper is on formulating our scheduling problem as a special type of vehicle routing with pickup and delivery problem. We propose a new set partitioning model of our specific problem. Vehicle routes are defined on the graph of cities, rather than on the graph of customer orders, as typically proposed by set partitioning formulations. This approach is particularly useful when a large number of customer orders sharing a significantly lower number of pickup and delivery points must be scheduled. Our achievement is the declarative representation and solution of the model using ECLiPSe state-of-the-art constraint logic programming system. (C) 2017 The Authors. Published by Elsevier B.V.
引用
收藏
页码:958 / 967
页数:10
相关论文
共 13 条
[1]  
[Anonymous], 2004, OPERATIONS RES APPL
[2]  
[Anonymous], 2008, J BETRIEBSWIRTSCHAFT, DOI DOI 10.1007/S11301-008-0036-4
[3]   Optimization by hybridization of a genetic algorithm with constraint satisfaction techniques [J].
Barnier, N ;
Brisset, P .
1998 IEEE INTERNATIONAL CONFERENCE ON EVOLUTIONARY COMPUTATION - PROCEEDINGS, 1998, :645-649
[4]   A comparison of CLP(FD) and ASP solutions to NP-complete problems [J].
Dovier, A ;
Formisano, A ;
Pontelli, E .
LOGIC PROGRAMMING, PROCEEDINGS, 2005, 3668 :67-82
[5]   Constraint logic programming [J].
Gavanelli M. ;
Rossi F. .
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2010, 6125 :64-86
[6]  
Gouidis F, 2014, LECT NOTES ARTIF INT, V8445, P489, DOI 10.1007/978-3-319-07064-3_42
[7]  
Holldobler Steffen, 2012, KI 2012: Advances in Artificial Intelligence. Proceedings of the 35th Annual German Conference on AI, P107, DOI 10.1007/978-3-642-33347-7_10
[8]   A Freight Brokering System Architecture Based on Web Services and Agents [J].
Leon, Florin ;
Badica, Costin .
EXPLORING SERVICES SCIENCE (IESS 2016), 2016, 247 :537-546
[9]  
Luncean L, 2014, LECT NOTES ARTIF INT, V8398, P485, DOI 10.1007/978-3-319-05458-2_50
[10]  
NIEDERLINSKI A, 2014, GENTLE GUIDE CONSTRA