The \(\alpha \)-cost minimization model for capacitated facility location-allocation problem with uncertain demands
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.
location-allocation problem uncertainty theory uncertain variable genetic algorithm