An Efficient Metaheuristic Approach for the Multi-Period Technician Routing and Scheduling Problem

A. Khattara, W. R. Cherif-Khettaf, M. Mostefai


In this paper, we address a new variant of the Multi-Period Technician Routing and Scheduling Problem. This problem is motivated by a real-life industrial application in a telecommunication company. It is defined by a set of technicians having distinct skills that could perform a set of geographically scattered tasks over a multi-period horizon. Each task is subject to time constraints and must be done at most once over the horizon by one compatible technician. The objective is to minimize the total working time (composed by routing time, service time, and waiting time), the total cost engendered by the rejected tasks, and the total delay. Two variants of variable neighborhood descent are proposed, and three variants of variable neighborhood search to solve this problem. Computational experiments are conducted on benchmark instances from the literature. An analysis of the performance of the proposed local search procedures is given. The results show that our methods outperform the results of a mimetic method published in the literature.


technician routing and scheduling problem (TRSP); variable neighborhood search (VNS); variable neighborhood descent (VND)

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