Multi-objective optimisation of facility location decisions within integrated forward/reverse logistics under uncertainty

Abstract

Increasing interest to the environmental, social and economic aspects of the supply chains has motivated supply chain managers to optimise location-allocation decisions within closed-loop logistics networks. This paper presents a multi-objective model to optimise facility location decisions in integrated forward/reverse streams under uncertainty. The objectives of the model are to minimise total costs and simultaneously maximise customer satisfaction considering uncertainties in demand and return rate. The proposed model is solved by integrating genetic algorithm with sampling average method. The application of the model is examined in a real case study of car after sales network. The result of the model is compared to a deterministic model to identify how uncertainties affect the optimal configurations. The other experiment is carried out to study the effect of integrating forward and reverse logistics operations on the stakeholder's objectives. Finally, a post-analysis is applied to help in choosing one solution among many different solutions. 2016 Inderscience Enterprises Ltd.