Total Cost Minimization Transportation Problem – A Case Study of Carl Star

R. Agarwal, Piyusha S. Somvanshi
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引用次数: 1

Abstract

Optimization models can be used to determine the lowest cost solution to ship products from the manufacturing origin to the end customer. This Capstone developed a mixed integer linear programming model for Carl star, a global leader in the specialty tire and wheel industry. The objective was to identify the optimal routing solution of problem to minimize total cost transportation and tariff costs for each of the company’s five product market segments. The model provided for multiple possible routing options, including shipping direct to the customer from the manufacturer or through a distribution center. Multiple scenarios were run using different rates for transportation costs, tariffs, and customer demand. Model constraints included manufacturing location, demand, and flow balance through the distribution centers. Results indicate that Carl star could save almost 20% on distribution costs by increasing the number of direct to customer shipments. The impacts of tariffs demand fluctuations and handling costs were smaller than expected, indicating that once an updated transportation network is established, it would not have to be updated very often to maximize potential cost savings.
总成本最小化运输问题-以卡尔·斯达为例
优化模型可用于确定将产品从制造地运送到最终客户的最低成本解决方案。Capstone为全球特种轮胎和车轮行业的领导者卡尔斯达开发了一个混合整数线性规划模型。目标是确定问题的最佳路线解决方案,以最小化公司五个产品细分市场的总运输成本和关税成本。该模型提供了多种可能的路线选择,包括从制造商直接向客户发货或通过配送中心发货。使用运输成本、关税和客户需求的不同费率运行多个场景。模型约束包括制造位置、需求和通过配送中心的流量平衡。结果表明,通过增加直接向客户发货的数量,Carl star可以节省近20%的配送成本。关税、需求波动和处理成本的影响比预期的要小,这表明,一旦建立了更新的运输网络,就不必经常更新,以最大限度地节省潜在的成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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