IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

An Efficient VNS Algorithm to Solve the Multi-Attribute Technician Routing and Scheduling Problem

An Efficient VNS Algorithm to Solve the Multi-Attribute Technician Routing and Scheduling Problem
View Sample PDF
Author(s): Sana Frifita (Laboratory of Modeling and Optimization for Decisional, Industrial and Logistic Systems (MODILS), Sfax, Tunisia), Ines Mathlouthi (Department of Computer Science and Operations Research, University of Montreal, Canada) and Abdelaziz Dammak (Laboratory of Modeling and Optimization for Decisional, Industrial and Logistic Systems (MODILS), Sfax, Tunisia)
Copyright: 2020
Volume: 11
Issue: 1
Pages: 13
Source title: International Journal of Applied Metaheuristic Computing (IJAMC)
Editor(s)-in-Chief: Peng-Yeng Yin (National Chi Nan University, Taiwan)
DOI: 10.4018/IJAMC.2020010102

Purchase

View An Efficient VNS Algorithm to Solve the Multi-Attribute Technician Routing and Scheduling Problem on the publisher's website for pricing and purchasing information.

Abstract

This article addresses a technician routing and scheduling problem inspired from an application for the repair of electronic transactions equipment. It consists of designing routes for staff to perform requests while considering certain constraints and resources. The objective is to minimize a linear combination of total weighted distance, overtime, and maximize the served requests. An efficient meta-heuristic algorithm based on variable neighborhood search with an adaptive memory and advanced diversity management method is proposed. Numerical results show that the meta-heuristic outperforms the best existing algorithm from the literature which is a Tabu Search.

Related Content

Hassene Faiedh, Wajdi Farhat, Sabrine Hamdi, Chokri Souani. © 2020. 22 pages.
Pankaj P. Prajapati, Mihir V. Shah. © 2020. 9 pages.
Méziane Aïder, Asma Skoudarli. © 2020. 22 pages.
Pandian Vasant, Fahad Parvez Mahdi, Jose Antonio Marmolejo-Saucedo, Igor Litvinchev, Roman Rodriguez Aguilar, Junzo Watada. © 2020. 17 pages.
Patrick Kenekayoro, Promise Mebine, Bodouowei Godswill Zipamone. © 2020. 16 pages.
Dalia Fendri, Maher Chaabene. © 2020. 12 pages.
Sana Frifita, Ines Mathlouthi, Abdelaziz Dammak. © 2020. 13 pages.
Body Bottom