| Summary: | 碩士 === 國立交通大學 === 運輸科技與管理學系 === 99 === Researchers are interested in studying the joint replenishment Problem due to its applications in the globalization of markets and products diversification. Also, the practitioners are motivated to reduce the total costs by replenishing products jointly. The costs in the traditional Joint Replenishment Problem are composed of three parts：(1) major setup cost, (2) minor setup cost and (3) inventory holding cost. This study focused on additionally taking into account the transportation cost subject to using a fixed basic period for the planning of replenishment. We formulate a mathematic model by including the above costs in this study. We propose a genetic algorithm (GA) that was equipped with a local search to effectively obtain the best replenishment multiplier value, the best replenishment schedule and the container numbers. Using our random experiments, we compare the proposed GA with LINGO and the Common Cycle Approach, and conclude that the proposed GA is able to efficiently obtain better solutions than the others.
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