A self-adaptive differential evolution for the technician routing and scheduling problem

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Published: May 24, 2023
Keywords:
Technician scheduling Vehicle routing Differential evolution

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Voravee Punyakum
Faculty of Technical Education, Rajamangala University of Technology Krungthep, Bangkok 10120, Thailand
Krisanarach Nitisiri
Research Unit on System Modelling for Industry, Department of Industrial Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen 40002, Thailand
Kanchana Sethanan
Research Unit on System Modelling for Industry, Department of Industrial Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen 40002, Thailand
Dusit Singpommat
Faculty of Technical Education, Rajamangala University of Technology Krungthep, Bangkok 10120, Thailand

Abstract

This paper presents two approaches for solving the Technician Routing and Scheduling Problem (TRSP). The first approach is an integer programming method, and the second is a Self-Adaptive Differential Evolution (SADE) algorithm. The TRSP involves scheduling jobs for service teams who have different skill sets. These jobs have time constraints and can only be completed by technicians with the necessary skills. The goal of the TRSP is to minimize the operating cost, which includes travel, late service penalties, technician overtime, and subcontracting costs. To evaluate the effectiveness of the proposed SADE and integer programming approaches, we conducted small-scale numerical experiments. We also compared the performance of SADE to that of the conventional Differential Evolution (DE) algorithm on medium and large-scale problems. The results indicate that SADE produces significantly higher quality solutions compared to DE.

Article Details

How to Cite
Punyakum, V., Nitisiri, K., Sethanan, K. ., & Singpommat, D. . (2023). A self-adaptive differential evolution for the technician routing and scheduling problem. Engineering and Applied Science Research, 50(3), 262–269. Retrieved from https://ph01.tci-thaijo.org/index.php/easr/article/view/251019
Issue
Vol. 50 No. 3 (2023)
Section
ORIGINAL RESEARCH
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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