Parallel computation for production and distribution planning

Abstract

Due to the TFT LCD (Thin-Film-Transistor Liquid-Crystal-Display) manifestation into many related products, this industry has been growing rapidly along with increasing demand. To satisfy the demand, most companies have increased their production capacity and capability by increasing their number of factories in different places and causing complexity in this industry. This research develops a production and distribution planning model for the multi-stage and multi-site supply chain in the TFT LCD industry. Genetic algorithm proposed in this research to solve the problem. Maximizing capacity utilization and total profit in the supply chain are become the major performance indicator in this model. Regarding the high computational effort of genetic algorithm, then parallel computation performed. Genetic algorithm conducted in multi-processor computation using OpenMP for time efficiency. To compare the computational time, the genetic algorithm conducted in five different number of processors; 1, 2, 4, 8, and 16, to know how many processors are needed to get the optimal computational time. The result is the genetic algorithm using 4 processors has the optimal expected net profit compare to the others. The result shows that a larger number of processors doesn’t mean the computation time will become automatically faster.