Abstract
Improper value of the parameter p in robust constraints will result in no feasible solutions while applying stochastic p-robustness optimization approach (p-SRO) to solving facility location problems under uncertainty. Aiming at finding the lowest critical p-value of parameter p and corresponding robust optimal solution, we developed a novel robust optimization approach named as min-p robust optimization approach (min-pRO) for P-median problem (PMP) and fixed cost P-median problem (FPMP). Combined with the nearest allocation strategy, the vertex substitution heuristic algorithm is improved and the influencing factors of the lowest critical p-value are analyzed. The effectiveness and performance of the proposed approach are verified by numerical examples. The results show that the fluctuation range of data is positively correlated with the lowest critical p-value with given number of new facilities. However, the number of new facilities has a different impact on lowest critical p-value with the given fluctuation range of data. As the number of new facilities increases, the lowest critical p-value for PMP and FPMP increases and decreases, respectively.
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Acknowledgements
This research was supported by National Natural Science Foundation of China (41671396), Scientific Research Foundation for PhD of GNNU (BSJJ202116) and Guizhou Theoretical Innovation Joint Project of China (GZLCLH-2020-331, GZLCLH-2021-86).
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Lai, Z., Yue, Q., Wang, Z. et al. The min-p robust optimization approach for facility location problem under uncertainty. J Comb Optim 44, 1134–1160 (2022). https://doi.org/10.1007/s10878-022-00868-9
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DOI: https://doi.org/10.1007/s10878-022-00868-9