Planning a selective delivery schedule through Adaptive Large Neighborhood Search

Pamela Jocelyn Palomo Martinez; M. Angélica Salazar-Aguilar; Gilbert Laporte

doi:10.1016/j.cie.2017.08.037

Planning a selective delivery schedule through Adaptive Large Neighborhood Search

Pamela Jocelyn Palomo Martinez, M. Angélica Salazar-Aguilar, Gilbert Laporte

Research output: Contribution to journal › Article › peer-review

7 Citations (Scopus)

Abstract

We model and solve a real-life distribution problem faced by a fresh fruit supplier. This problem is formulated as a Multi-Product Split Delivery Capacitated Team Orienteering Problem with Incomplete Service and Soft Time Windows. The problem is modeled through a mixed integer linear programming formulation and solved by an Adaptive Large Neighborhood Search (ALNS) metaheuristic. Computational results over a large set of artificial instances show that the combination of ALNS with a multi-start scheme produces better results than a classical implementation of the ALNS in which a single solution is built and improved.

Original language	English
Pages (from-to)	368-378
Number of pages	11
Journal	Computers and Industrial Engineering
Volume	112
DOIs	https://doi.org/10.1016/j.cie.2017.08.037
Publication status	Published - Oct 2017
Externally published	Yes

Bibliographical note

Funding Information:
This work was supported by CONACYT and the Canadian Natural Sciences and Engineering Research Council under grant 2015-06189. This support is gratefully acknowledged. Thanks are due to the referee who provided valuable comments on an earlier version of this paper.

Publisher Copyright:
© 2017 Elsevier Ltd

Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.

All Science Journal Classification (ASJC) codes

Computer Science(all)
Engineering(all)

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10.1016/j.cie.2017.08.037

Cite this

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title = "Planning a selective delivery schedule through Adaptive Large Neighborhood Search",

abstract = "We model and solve a real-life distribution problem faced by a fresh fruit supplier. This problem is formulated as a Multi-Product Split Delivery Capacitated Team Orienteering Problem with Incomplete Service and Soft Time Windows. The problem is modeled through a mixed integer linear programming formulation and solved by an Adaptive Large Neighborhood Search (ALNS) metaheuristic. Computational results over a large set of artificial instances show that the combination of ALNS with a multi-start scheme produces better results than a classical implementation of the ALNS in which a single solution is built and improved.",

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doi = "10.1016/j.cie.2017.08.037",

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AU - Salazar-Aguilar, M. Angélica

AU - Laporte, Gilbert

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AB - We model and solve a real-life distribution problem faced by a fresh fruit supplier. This problem is formulated as a Multi-Product Split Delivery Capacitated Team Orienteering Problem with Incomplete Service and Soft Time Windows. The problem is modeled through a mixed integer linear programming formulation and solved by an Adaptive Large Neighborhood Search (ALNS) metaheuristic. Computational results over a large set of artificial instances show that the combination of ALNS with a multi-start scheme produces better results than a classical implementation of the ALNS in which a single solution is built and improved.

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ER -

Planning a selective delivery schedule through Adaptive Large Neighborhood Search

Abstract

Bibliographical note

All Science Journal Classification (ASJC) codes

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