A heterogeneous reliable location model with risk pooling under supply disruptions

Ying Zhang, Lawrence V. Snyder, Mingyao Qi and Lixin Miao

Transportation Research Part B: Methodological, 2016, vol. 83, issue C, 151-178

Abstract: This paper investigates a facility location model that considers the disruptions of facilities and the cost savings from the inventory risk-pooling effect and economies of scale. Facilities may have heterogeneous disruption probabilities. When a facility fails, its customers may be reassigned to other surviving ones to hedge against lost-sales costs. We first develop both an exact and an approximate expression for the nonlinear inventory cost, and then formulate the problem as a nonlinear integer programming model. The objective is to minimize the expected total cost across all possible facility failure scenarios. To solve this problem, we design two methods, an exact approach using special ordered sets of type two (SOS2) and a heuristic based on Lagrangian relaxation. We test the model and algorithms on data sets with up to 150 nodes. Computational results show that the proposed algorithms can solve the problem efficiently in reasonable time. Managerial insights on the optimal facility deployment, customer assignments and inventory control strategies are also drawn.

Keywords: Facility location; Disruption; Risk pooling; Concave minimization; Lagrangian relaxation (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)

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DOI: 10.1016/j.trb.2015.11.009

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