Reliable Facility Location Under Risk of Disruptions
2009
In the reliable facility location models context, facilities are subject to unexpected failure and customers may have to be reassigned from their regular facility to others that require excessive transportation cost. This paper proposes a linear mixed integer program (MIP) model and a continuum approximation (CA) model to study the reliable uncapacitated fixed charge location problem (RUFL), where the objective is to minimize initial setup costs and expected transportation costs in normal and failure scenarios. The MIP model finds the optimal facility locations as well as the customer assignments, allowing facilities to have varying failure probabilities. A custom designed Lagrangian relaxation algorithm is proposed to solve the MIP model efficiently. The CA model accurately predicts the total system cost without details of facility locations and customer assignments. In addition to providing managerial insights (i.e., solution robustness to input data errors, and advantage of having diversity in facility types), the CA model also serves as a very efficient heuristic method to find near-optimum discrete solutions. Extensive numerical results show that the proposed Lagrangian relaxation algorithm solves the MIP model quite efficciently. The CA model provides a very good alternative especially for large-scale problem instances when the discrete model fails to solve in a reasonable amount of time.
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