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Time-reliability optimization for the stochastic traveling salesman problem

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  • Yeh, Wei-Chang

Abstract

This paper presents a novel approach to addressing the Stochastic Traveling Salesman Problem (STSP), a classical problem in combinatorial optimization, by integrating travel time and reliability factors into the decision-making process. Traditional TSP models primarily focus on minimizing the total travel distance or cost without considering the reliability of each route. In real-world situations, especially in logistics and network design, it's just as important to have reliable routes. A reliable route means there's a good chance it will be completed successfully and on time. Our research extends the conventional STSP framework by incorporating a reliability metric for each route, alongside the standard travel time metric. A tri-objective optimization model is proposed to minimize the mean and standard deviation of travel time and maximize route reliability simultaneously. A new algorithm called Permutation Binary-Addition-Tree (BAT) is proposed to solve the problem more efficiently when there is uncertainty. Our approach marks a significant step towards more realistic and practical solutions for route optimization problems in dynamic and uncertain environments. We also present a complexity analysis of our model against traditional cost-only TSP solutions, demonstrating the efficacy of considering reliability in route planning.

Suggested Citation

  • Yeh, Wei-Chang, 2024. "Time-reliability optimization for the stochastic traveling salesman problem," Reliability Engineering and System Safety, Elsevier, vol. 248(C).
    • Handle: RePEc:eee:reensy:v:248:y:2024:i:c:s0951832024002539
    DOI: 10.1016/j.ress.2024.110179
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    References listed on IDEAS

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    1. Yeh, Wei-Chang & Tan, Shi-Yi & Zhu, Wenbo & Huang, Chia-Ling & Yang, Guang-yi, 2022. "Novel binary addition tree algorithm (BAT) for calculating the direct lower-bound of the highly reliable binary-state network reliability," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
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    5. Yeh, Wei-Chang, 2023. "Novel recursive inclusion-exclusion technology based on BAT and MPs for heterogeneous-arc binary-state network reliability problems," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    6. Pop, Petrică C. & Cosma, Ovidiu & Sabo, Cosmin & Sitar, Corina Pop, 2024. "A comprehensive survey on the generalized traveling salesman problem," European Journal of Operational Research, Elsevier, vol. 314(3), pages 819-835.
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    11. Khakzad, Nima, 2023. "A goal programming approach to multi-objective optimization of firefighting strategies in the event of domino effects," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
    12. Yeh, Wei-Chang, 2024. "A new hybrid inequality BAT for comprehensive all-level d-MP identification using minimal paths in Multistate Flow Network reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    13. Wei-Chang Yeh & Edward Lin & Chia-Ling Huang & Luxing Yang, 2021. "Predicting Spread Probability of Learning-Effect Computer Virus," Complexity, Hindawi, vol. 2021, pages 1-17, July.
    14. Hao, Zhifeng & Yeh, Wei-Chang & Liu, Zhenyao & Forghani-elahabad, Majid, 2020. "General multi-state rework network and reliability algorithm," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    15. Forghani-elahabad, Majid & Yeh, Wei-Chang, 2022. "An improved algorithm for reliability evaluation of flow networks," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    16. Yeh, Wei-Chang, 2022. "Novel self-adaptive Monte Carlo simulation based on binary-addition-tree algorithm for binary-state network reliability approximation," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    17. Yeh, Wei-Chang, 2006. "The k-out-of-n acyclic multistate-node networks reliability evaluation using the universal generating function method," Reliability Engineering and System Safety, Elsevier, vol. 91(7), pages 800-808.
    18. Wang, Huan & Li, Yan-Fu, 2023. "Bioinspired membrane learnable spiking neural network for autonomous vehicle sensors fault diagnosis under open environments," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    19. Zhi Chen & Peng Xiong, 2023. "RSOME in Python: An Open-Source Package for Robust Stochastic Optimization Made Easy," INFORMS Journal on Computing, INFORMS, vol. 35(4), pages 717-724, July.
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