Abstract
The stochastic resource allocation problem with time windows (SRAPTW) refers to a class of combinatorial optimization problems which are aimed at finding the optimal scheme of assigning resources to given tasks within their time windows. In SRAPTW, the capability of resources to accomplish tasks is quantitatively characterized by probability. The expected allocation scheme should include not only the task-resource pairings but also their allocation time. This paper formulates SRAPTW as a nonlinear mixed 0–1 programming problem with the objective of maximizing the reward of completing specified tasks. Then, a general encoding/decoding method is proposed for the representation of solutions, and several different problem-solving methodologies are presented and compared. Results of computational experiments show that the utilization of SRAPTW-specific knowledge can bring in excellent performance, and a constructive heuristic combining maximal marginal return strategy and maximal probability strategy has remarkable advantages, especially in larger-scale cases.
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Acknowledgement
We would like to thank the National Outstanding Youth Talents Support Program (Grant 61822304), the Basic Science Center Programs of NSFC (Grant 62088101), the Shanghai Municipal Science and Technology Major Project (2021SHZDZX0100), and the Shanghai Municipal Commission of Science and Technology Project (19511132101).
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Li, Y., Xin, B. (2024). Stochastic Resource Allocation with Time Windows. In: Xin, B., Kubota, N., Chen, K., Dong, F. (eds) Advanced Computational Intelligence and Intelligent Informatics. IWACIII 2023. Communications in Computer and Information Science, vol 1931. Springer, Singapore. https://doi.org/10.1007/978-981-99-7590-7_28
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DOI: https://doi.org/10.1007/978-981-99-7590-7_28
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