Abstract

In the supply chain design problems, optimization is usually done without any attention to performance and efficiency of each part of chain. On the other hand, in Assembly Line Balancing (ALB) problems, the objective of the problems is to optimize with regard to the situation of assemblers, while in this set of problems, concentration on some factors such as how to provide raw materials and also sending final products to customers are very important. Since optimal decisions in each problem will affect the other decisions, it is required to study these two matters at the same time; otherwise, the validity of the results will be reduced. In this paper, the problem of integration of multi-product Supply Chain Network designing and ALB are addressed. A Mixed Integer Nonlinear Programming model is proposed to formulate the studied problem. The model is solved by using GAMS in the form of a numerical example given in small size. Finally, Imperialist Competitive Algorithm (ICA) and Genetic Algorithm (GA) as two well-known meta-heuristic algorithms are applied to solve the model with larger dimensions. The computational results show efficiency of the ICA compared with GA. Moreover, after decomposing the integrated mode into two sub problems (ALB problem and Supply Chain Network Design problem), it is shown that optimum cost value of integrated mode is better than total cost functions of two sub-problems separately.

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