A Multi-objective Resource Assignment Problem in Product Driven Supply Chain Using Quantum Inspired Particle Swarm Algorithm

Abstract

This chapter presents a novel approach that integrates the intangible factors with the tangible ones to model the resource assignment problem in a product driven supply chain. The problem has been mathematically modeled as a multi-objective optimization problem with the objectives of profit, quality, ahead time of delivery and volume flexibility. In this research, product characteristics have been associated with the design requirements of a supply chain. Different types of resources have been considered each differing in its characteristics, thereby providing various alternatives during the design process. The aim is to design integrated supply chains that maximizes the weighted sum of the objectives, the weights being decided by the desired product characteristics. The problem has been solved through a proposed Quantum inspired Particle Swarm Optimization (QPSO) metaheuristic. It amalgamates particle swarm optimization with quantum mechanics to enhance the search potential and make it suitable for integer valued optimization. The performance of the proposed solution methodology and its three variants has been authenticated over a set of test instances. The results of the above study and the insights derived through it validate the efficiency of the proposed model as well as the solution methodology on the problem at hand.