Solving the Flying Sidekick Traveling Salesman Problem by a Simulated Annealing Heuristic

Author:

Yu Vincent F.12ORCID,Lin Shih-Wei345ORCID,Jodiawan Panca1,Lai Yu-Chi6ORCID

Affiliation:

1. Department of Industrial Management, National Taiwan University of Science and Technology, Taipei 106335, Taiwan

2. Center for Cyber-Physical System Innovation, National Taiwan University of Science and Technology, Taipei 106335, Taiwan

3. Department of Information Management, Chang Gung University, Taoyuan 33302, Taiwan

4. Department of Industrial Engineering and Management, Ming Chi University of Technology, New Taipei 243303, Taiwan

5. Department of Emergency Medicine, Keelung Chang Gung Memorial Hospital, Keelung 20401, Taiwan

6. Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei 106335, Taiwan

Abstract

This study investigates the flying sidekick traveling salesman problem (FSTSP), in which a truck and an unmanned aerial vehicle work together to make deliveries. This study develops a revised mixed-integer linear programming (MILP) model for the FSTSP. The revised MILP model performs better than the existing model. Due to the FSTSP’s high complexity, we propose an effective heuristic based on simulated annealing (SA) to solve the problem. The novelty of the proposed SA heuristic lies in the new solution representation, which not only determines the visiting sequence of customers but also the service type of customers and rendezvous positions. Another feature of the proposed SA is a new operator specifically designed for the FSTSP. To evaluate the performance of the proposed SA heuristic, we conduct a comprehensive computational study where we fine-tune the parameters of the SA heuristic and compare the performance of the SA heuristic with several state-of-the-art algorithms including hybrid genetic algorithm (HGA) and iterated local search (ILS) in solving existing FSTSP benchmark instances. The results indicate that the proposed SA heuristic outperforms ILS and is statistically competitive with HGA. It obtains best-known solutions for all small FSTSP instances and 29 best-known solutions for the 60 large FSTSP instances, including 20 new best-known solutions.

Funder

Ministry of Science and Technology of the Republic of China

Center for Cyber-Physical System Innovation from the Featured Areas Research Center Program within the framework of the Higher Education Sprout Project

Chang Gung Memorial Hospital

Publisher

MDPI AG

Subject

General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)

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