Abstract
Facility location-allocation problem aims at determining the locations of some facilities to serve a set of spatially distributed customers and the allocation of each customer to the facilities such that the total transportation cost is minimized. In real life, the facility location-allocation problem often comes with uncertainty for lack of the information about the customers’ demands. Within the framework of uncertainty theory, this paper proposes an uncertain facility location-allocation model by means of chance-constraints, in which the customers’ demands are assumed to be uncertain variables. An equivalent crisp model is obtained via the \(\alpha \)-optimistic criterion of the total transportation cost. Besides, a hybrid intelligent algorithm is designed to solve the uncertain facility location-allocation problem, and its viability and effectiveness are illustrated by a numerical example.
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Acknowledgments
This work was supported by National Natural Science Foundation of China (Nos. 71201005, 71371019, 61104132), and in part by the Program for New Century Excellent Talents in University (No. NCET-12-0026).
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Wen, M., Qin, Z. & Kang, R. The \(\alpha \)-cost minimization model for capacitated facility location-allocation problem with uncertain demands. Fuzzy Optim Decis Making 13, 345–356 (2014). https://doi.org/10.1007/s10700-014-9179-z
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DOI: https://doi.org/10.1007/s10700-014-9179-z