A Modified Particle Swarm Optimization Algorithm for Solving Capacitated Maximal Covering Location Problem in Healthcare Systems
Location allocation decision of special facilities in healthcare is an emergent topic that is gaining noticeable attention especially in developing countries. Given the high cost of such facilities and the need to cover as much demand as possible, systematic methods are needed to be used to handle such a problem. In this chapter, a Capacitated Maximal Covering Location Problem (CMCLP) is used in order to model this problem. A proposed modified Particle Swarm Optimization (PSO) algorithm is used to solve the CMCLP. The solutions of the modified PSO algorithm is compared to GAMS outcomes, showing much better results. The proposed algorithm denotes promised results in pinpointing good locations for the facility maximizing the covered demand.
Applications of Intelligent Optimization in Biology and Medicine