Integrated aggregate supply chain planning using Memetic Algorithm—a performance analysis case study

Behnam Fahimnia, Reza Zanjirani Farahani, and Joseph Sarkis

International Journal of Production Research, Forthcoming.

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

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