A hybrid approach to solve a raw material collecting vehicle routing problem

IF 4.5 Q1 MANAGEMENT
Anurag Tiwari, P. Mohapatra
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引用次数: 0

Abstract

PurposeThe purpose of this study is to formulate a new class of vehicle routing problem with an objective to minimise the total cost of raw material collection and derive a new approach to solve optimization problems. This study can help to select the optimum number of suppliers based on cost.Design/methodology/approachTo model the raw material vehicle routing problem, a mixed integer linear programming (MILP) problem is formulated. An interesting phenomenon added to the proposed problem is that there is no compulsion to visit all suppliers. To guarantee the demand of semiconductor industry, all visited suppliers should reach a given raw material capacity requirement. To solve the proposed model, the authors developed a novel hybrid approach that is a combination of block and edge recombination approaches. To avoid bias, the authors compare the results of the proposed methodology with other known approaches, such as genetic algorithms (GAs) and ant colony optimisation (ACO).FindingsThe findings indicate that the proposed model can be useful in industries, where multiple suppliers are used. The proposed hybrid approach provides a better sequence of suppliers compared to other heuristic techniques.Research limitations/implicationsThe data used in the proposed model is generated based on previous literature. The problem derives from the assumption that semiconductor industries use a variety of raw materials.Practical implicationsThis study provides a new model and approach that can help practitioners and policymakers select suppliers based on their logistics costs.Originality/valueThis study provides two important contributions in the context of the supply chain. First, it provides a new variant of the vehicle routing problem in consideration of raw material collection; and second, it provides a new approach to solving optimisation problems.
一种混合方法解决原料收集车辆路线问题
本研究的目的是建立一类新的车辆路线问题,以最小化原材料收集的总成本为目标,并推导出一种新的方法来解决优化问题。该研究有助于基于成本选择最优供应商数量。设计/方法/途径为了对原材料车辆的路径问题进行建模,提出了一个混合整数线性规划(MILP)问题。在提出的问题之外,还增加了一个有趣的现象,即没有强制要求访问所有供应商。为了保证半导体行业的需求,所有访问的供应商必须达到给定的原材料产能要求。为了解决所提出的模型,作者开发了一种新的混合方法,即块和边缘重组方法的结合。为了避免偏差,作者将提出的方法的结果与其他已知方法(如遗传算法(GAs)和蚁群优化(ACO))进行了比较。研究结果表明,所提出的模型在使用多个供应商的行业中是有用的。与其他启发式技术相比,所提出的混合方法提供了更好的供应商序列。研究的局限性/意义所提出的模型中使用的数据是基于以前的文献生成的。这个问题源于半导体工业使用多种原材料的假设。本研究提供了一个新的模型和方法,可以帮助从业者和决策者根据物流成本选择供应商。原创性/价值本研究在供应链的背景下提供了两个重要贡献。首先,提出了一种考虑原材料回收的车辆路径问题的新变体;其次,它为解决优化问题提供了一种新的方法。
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来源期刊
CiteScore
10.40
自引率
16.10%
发文量
154
期刊介绍: Benchmarking is big news for companies committed to total quality programmes. Its enthusiastic reception by many prominent business figures has created high levels of interest in a technique which promises big rewards for co-operating partners. Yet, like total quality itself, it must be understood in its proper context, and implemented single mindedly if it is to be effective - this journal helps companies to decide if benchmarking is right for them, and shows them how to go about it successfully.
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