Abstract
In the Heterogeneous Robots Task Scheduling (HTS) problem, multiple transport robots and multiple pick robots collaborate to achieve complex-schedule order-fulfillment tasks, and we want to obtain the collective time-extended task schedule with the minimization of makespan. As a typical strongly NP-hard integrated routing and scheduling problem, metaheuristics are almost the only way to obtain near-optimal solutions within reasonable computation time. We design simulated annealing algorithms to improve initial solutions, and test three neighborhood operators. Extensive computational results demonstrate that simulated annealing could improve the solution quality for most problem instances, and the adjacent pairwise interchange (API) neighborhood operator is highly recommended.
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Acknowledgment
This work is supported by the National Natural Science Foundation of China (Grant U1813206) and the National Key R&D Program of China (Grant 2017YFB1303600).
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Wang, H., Chen, W. (2022). Simulated Annealing Algorithms for the Heterogeneous Robots Task Scheduling Problem in Heterogeneous Robotic Order Fulfillment Systems. In: Ang Jr, M.H., Asama, H., Lin, W., Foong, S. (eds) Intelligent Autonomous Systems 16. IAS 2021. Lecture Notes in Networks and Systems, vol 412. Springer, Cham. https://doi.org/10.1007/978-3-030-95892-3_21
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DOI: https://doi.org/10.1007/978-3-030-95892-3_21
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