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

Sana Frifita, Ines Mathlouthi and Abdelaziz Dammak
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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
Abdelaziz Dammak: Laboratory of Modeling and Optimization for Decisional, Industrial and Logistic Systems (MODILS), Sfax, Tunisia

International Journal of Applied Metaheuristic Computing (IJAMC), 2020, vol. 11, issue 1, 23-35

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.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jamc00:v:11:y:2020:i:1:p:23-35

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