Optimizing the multiple trip vehicle routing plan for a licensee green tea dealer in Sri Lanka

Thakshila Samarakkody, Heshan Alagalla
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引用次数: 1

Abstract

PurposeThis research is designed to optimize the business process of a green tea dealer, who is a key supply chain partner of the Sri Lankan tea industry. The most appropriate trips for each vehicle in multiple trip routing systems are identified to minimize the total cost by considering the traveling distance.Design/methodology/approachThe study has followed the concepts in vehicle routing problems and mixed-integer programming mathematical techniques. The model was coded with the Python programming language and was solved with the CPLEX Optimization solver version 12.10. In total, 20 data instances were used from the subjected green tea dealer for the validation of the model.FindingsThe result of the numerical experiment showed the ability to access supply over the full capacity of the available fleet. The model achieved optimal traveling distance for all the instances, with the capability of saving 17% of daily transpiration cost as an average.Research limitations/implicationsThis study contributes to the three index mixed-integer programing model formulation through in-depth analysis and combination of several extensions of vehicle routing problem.Practical implicationsThis study contributes to the three index mixed-integer programming model formulation through in-depth analysis and combination of several extensions of the vehicle routing problem.Social implicationsThe proposed model provides a cost-effective optimal routing plan to the green tea dealer, which satisfies all the practical situations by following the multiple trip vehicle routing problems. Licensee green tea dealer is able to have an optimal fleet size, which is always less than the original fleet size. Elimination of a vehicle from the fleet has the capability of reducing the workforce. Hence, this provides managerial implication for the optimal fleet sizing and route designing.Originality/valueDeveloping an optimization model for a tea dealer in Sri Lankan context is important, as this a complex real world case which has a significant importance in export economy of the country and which has not been analyzed or optimized through any previous research effort.
优化斯里兰卡某持牌绿茶经销商的多行程车辆路线计划
本研究旨在对一家绿茶经销商的业务流程进行优化,该经销商是斯里兰卡茶叶行业的关键供应链合作伙伴。在多行程路线系统中,通过考虑行驶距离,确定每辆车最合适的行程,使总成本最小。设计/方法/方法本研究遵循了车辆路线问题和混合整数规划数学技术中的概念。采用Python编程语言对模型进行编码,并使用12.10版本的CPLEX优化求解器对模型进行求解。总共使用了来自受试绿茶经销商的20个数据实例来验证模型。结果:数值实验结果表明,在可用船队的全部容量上,获得供应的能力。该模型实现了所有实例的最优行驶距离,平均可节省17%的日蒸腾成本。研究局限/启示本研究通过对车辆路径问题的几个扩展的深入分析和结合,形成了三指标混合整数规划模型。实际意义本研究通过对车辆路径问题的几个扩展进行深入分析和结合,形成了三指标混合整数规划模型。社会意义所提出的模型通过遵循多行程车辆路线问题,为绿茶经销商提供了一个经济有效的最优路线方案,该方案满足所有实际情况。被许可绿茶经销商能够有一个最佳的车队规模,这总是小于原来的车队规模。从车队中取消一辆车可以减少劳动力。因此,这为优化机队规模和航线设计提供了管理意义。原创性/价值为斯里兰卡的茶叶经销商开发一个优化模型是很重要的,因为这是一个复杂的现实世界案例,对该国的出口经济具有重要意义,并且没有通过任何先前的研究工作进行分析或优化。
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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