Solving Facility Location-Allocation Problem with Zone-Dependent Fixed Cost using Modified Cooper’s Method

Abstract

Location analysis is a vital area within Operations Research that focuses on optimizing the placement of facilities and the allocation of customers to achieve a balance between service efficiency and cost reduction. This research examines the incapacitated multisource Weber problem, incorporating zone-dependent fixed costs, which adds complexity by considering regional cost differences. Since the multisource Weber Problem is classified as an NP-hard problem due to its complexity, therefore a heuristic technique named Modified Cooper’s method was proposed. Algorithm for the solution technique was coded using Python programming. Previously, research had been done to solve this problem using Simulated Annealing (SA), which is a meta-heuristic approach known for its global search capabilities. Modified Cooper’s method resulted in a total cost of 171.02, significantly lower than the 196.73 achieved through SA. This finding highlights the effectiveness and practicality of the Modified Cooper’s method in addressing location-allocation challenges with zone-dependent costs, providing valuable insights for sectors such as logistics and urban planning.