This paper aims to examine how a complex supply chain yields cost reduction benefits through the global integration of production and distribution decisions. The research is motivated by a complex real-life supply chain planning problem faced by a large automotive company. An aggregate production-distribution (P-D) planning model is presented via the integration of aggregate production plan and distribution plan. The P-D planning problem is formulated using Mixed Integer Nonlinear Programming and a Memetic Algorithm-based solution method is developed to solve the proposed model. The performance and effectiveness of the developed approach in achieving the P-D global optimization is investigated in the proposed case study through conducting experiments for comparing the numerical results from the proposed integrated approach with those of the typical non-integrated (hierarchical) P-D optimization.
Keywords: Supply Chain Management; Production-Distribution Planning; Integration; Global Optimization; Performance Analysis