Efficient GRASP based heuristics for the capacitated continuous location-allocation problem

This paper explores the np-hard capacitated continuous location-allocation problem, where the number of facilities to be located is specified and each of which has a constant capacity. Efficient greedy randomised adaptive search procedure (GRASP) based heuristics are proposed to tackle the problem.A scheme that applies the furthest distance rule (FDR) and self-adjusted threshold parameters to generate initial facility locations that are situated sparsely within GRASP framework is also put forward.The construction of the restricted candidate list (RCL) within GRASP is also guided by applying a concept of restricted regions that prevents new facility locations to be sited too close to the previous selected facility locations.The performance of the proposed GRASP heuristics is evaluated by conducting experiments using data sets taken from the literature typically used for the uncapacitated continuous location-allocation problem.The preliminary computational experiments show that the proposed methods provide encouraging solutions when compared to recently published papers.Some future research avenues on the subject are also briefly highlighted