A Genetic Algorithm for an Integrated Production Policy Under Time-vary Demand and Unit Price

Bing-Chang OUYANG

Abstract


Under time-varying demand and raw material purchase cost, this study investigates a genetic algorithm for an integrated production batch policy that considers the batch size of raw materials and finished goods simultaneously over a finite time horizon. A genetic algorithm (GA) with the chromosome of real number type to solve this problem is presented. Although, standard GA operators are used to generate new populations, the particular of this research is that we select one differentiate equation to develop a proposed production scheme. Then, calculate the total cost with this production scheme as the fitness function to evaluate the populations. In this paper, an explicit procedure to obtain an approximating solution is provided and numerical examples to illustrate the proposed model are shown as well.

Keywords


Integrated production batch policy, Time-vary demand, Time-vary unit cost, genetic algorithm, Inventory


DOI
10.12783/dtcse/mmsta2017/19673

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