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An exact algorithm for the three-dimensional loading capacitated vehicle routing problem

An exact algorithm for the three-dimensional loading capacitated vehicle routing problem The three-dimensional loading capacitated vehicle routing problem is a strong NP-hard problem. Most existing algorithms for the problem are heuristic or meta-heuristic algorithms. In this paper, an exact algorithm is proposed for the problem. For solving the loading sub-problem, we use an effective method to generate possible points for loading items, which greatly reduce the search scope. Then we proposed an exact algorithm witch iteratively calls a branch-and-bound algorithm based on set partition. The validity of the proposed algorithm is examined by comparing the present results with those of published algorithms using the same data. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Business Performance and Supply Chain Modelling Inderscience Publishers

An exact algorithm for the three-dimensional loading capacitated vehicle routing problem

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd. All rights reserved
ISSN
1758-9401
eISSN
1758-941X
DOI
10.1504/IJBPSCM.2012.050391
Publisher site
See Article on Publisher Site

Abstract

The three-dimensional loading capacitated vehicle routing problem is a strong NP-hard problem. Most existing algorithms for the problem are heuristic or meta-heuristic algorithms. In this paper, an exact algorithm is proposed for the problem. For solving the loading sub-problem, we use an effective method to generate possible points for loading items, which greatly reduce the search scope. Then we proposed an exact algorithm witch iteratively calls a branch-and-bound algorithm based on set partition. The validity of the proposed algorithm is examined by comparing the present results with those of published algorithms using the same data.

Journal

International Journal of Business Performance and Supply Chain ModellingInderscience Publishers

Published: Jan 1, 2012

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