Planning a selective delivery schedule through Adaptive Large Neighborhood Search

Pamela J. Palomo-Martínez; 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 J. Palomo-Martínez, M. Angélica Salazar-Aguilar, Gilbert Laporte

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

9 Citations (SciVal)

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

Keywords

Adaptive Large Neighborhood Search
Soft time windows
Split deliveries
Team orienteering problem

ASJC Scopus subject areas

General Computer Science
General Engineering

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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.",

keywords = "Adaptive Large Neighborhood Search, Soft time windows, Split deliveries, Team orienteering problem",

author = "Palomo-Mart{\'i}nez, {Pamela J.} and Salazar-Aguilar, {M. Ang{\'e}lica} and Gilbert Laporte",

year = "2017",

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AU - Palomo-Martínez, Pamela J.

AU - Salazar-Aguilar, M. Angélica

AU - Laporte, Gilbert

PY - 2017/10

Y1 - 2017/10

N2 - 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.

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.

KW - Adaptive Large Neighborhood Search

KW - Soft time windows

KW - Split deliveries

KW - Team orienteering problem

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M3 - Article

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SP - 368

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JO - Computers and Industrial Engineering

JF - Computers and Industrial Engineering

ER -

Planning a selective delivery schedule through Adaptive Large Neighborhood Search

Abstract

Keywords

ASJC Scopus subject areas

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