Genetic algorithms for coordinated scheduling of production and air transportation

A main issue in supply chain management is coordinating production and distribution decisions. To achieve effective logistics scheduling, it is critical to integrate these two functions and plan them in a coordinated way. The problem is to determine both production schedule and air transportation allocation of orders to optimize customer service at minimum total cost. In order to solve the given problem, two genetic algorithm (GA) approaches are developed. However, the effectiveness of most metaheuristic algorithms is significantly depends on the correct choice of parameters. Hence, a Taguchi experimental design method is applied to set and estimate the proper values of GAs parameters to improve their performance. For the purpose of performance evaluation of proposed algorithms, various problem sizes are utilized and the computational results of GAs are compared with each other. Moreover, we investigate the impacts of the rise in the problem size on the performance of our algorithms.

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