A branch-price-and-cut algorithm for the capacitated multiple vehicle traveling purchaser problem with unitary demand

被引:9
|
作者
Bianchessi, Nicola [1 ,2 ]
Irnich, Stefan [1 ]
Tilk, Christian [1 ]
机构
[1] Johannes Gutenberg Univ Mainz, Gutenberg Sch Management & Econ, Chair Logist Management, Jakob Welder Weg 9, D-55128 Mainz, Germany
[2] Univ Milan, Dipartimento Informat, Via Celoria 18, I-20122 Milan, Italy
关键词
Vehicle routing; Multiple vehicle traveling purchaser problem; Unitary demand; Incompatible products; Column generation; Dynamic-programming labeling algorithm; COLUMN GENERATION APPROACH; ROUTING PROBLEM; CONSTRAINTS; RELAXATION;
D O I
10.1016/j.dam.2020.08.014
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
The multiple vehicle traveling purchaser problem (MVTPP) consists of simultaneously selecting suppliers and routing a fleet of homogeneous vehicles to purchase different products at the selected suppliers so that all product demands are fulfilled and traveling and purchasing costs are minimized. We consider variants of the MVTPP in which the capacity of the vehicles can become binding and the demand for each product is one unit. Corresponding solution algorithms from the literature are either branch-and-cut or branch-and-price algorithms, where in the latter case the route-generation subproblem is solved on an expanded graph by applying standard dynamic-programming techniques. Our branch-price-and-cut algorithm employs a novel labeling algorithm that works directly on the original network and postpones the purchasing decisions until the route has been completely defined. Moreover, we define a new branching rule generally applicable in case of unitary product demands, introduce a new family of valid inequalities to apply when suppliers can be visited at most once, and show how product incompatibilities can be handled without considering additional resources in the pricing problem. In comprehensive computational experiments with standard benchmark sets we prove that the new branch-price-and-cut approach is highly competitive. (C) 2020 Elsevier B.V. All rights reserved.
引用
收藏
页码:152 / 170
页数:19
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