以食品行业为例，研究了物流优化中的车辆路线问题

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2021-09-30 DOI:10.17270/j.log.2021.604

M. E. Akpinar

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引用次数: 3

摘要

。背景:本研究以某食品公司所面临的食品配送问题为研究对象。该公司在七个不同的地区提供食品，每个地区都有一定数量的顾客。每位客人点餐的时间根据轮班情况而有所不同。这类问题在文献中被称为带时间窗的车辆路线问题，研究的主要目的是使车辆的总行驶距离最小。第二个目标是根据期望的用餐时间，通过使用最少的车辆来确定哪辆车将沿着该地区的哪条路线行驶。方法:本研究采用遗传算法方法求解该问题。元启发式算法用于包含多个组合且无法在合理时间内解决的问题。因此，本研究采用遗传算法的方法，在合理的时间内求解这一问题。这种方法的优点是通过尝试一定数量的种群的可能解来找到最合适的解。结果:研究中考虑了不同的人口规模。对每个种群进行1000次迭代。根据遗传算法的结果，在最小的种群规模下获得最佳结果。该方法使总距离缩短了约14%。此外，每个区域的车辆数量和哪些车辆将为谁服务也已确定。这项研究是一项现实应用，即使仅从这一地区，也为食品公司提供了可观的盈利能力。此外，七个地区的改善速度各不相同。顾客随时接受服务的能力最大限度地提高了顾客满意度，并提高了长期工作的能力。结论:本研究采用的方法和结果对该食品公司具有积极意义。然而，本研究中使用的元启发式算法并不能保证最优结果。因此，在未来的研究中可以考虑数学模型或仿真模型。此外，除了时间窗问题外，还可以考虑拾取问题，并制定不同的解决方案。

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A logistic optimization for the vehicle routing problem through a case study in the food industry

. Background: In this study, the food delivery problem faced by a food company is discussed. There are seven different regions where the company serves food and a certain number of customers in each region. The time of requesting food for each customer varies according to the shift situation. This type of problem is referred to as a vehicle routing problem with time windows in the literature and the main aim of the study is to minimize the total travel distance of the vehicles. The second aim is to determine which vehicle will follow which route in the region by using the least amount of vehicle according to the desired mealtime. Methods: In this study, genetic algorithm methodology is used for the solution of the problem. Metaheuristic algorithms are used for problems that contain multiple combinations and cannot be solved in a reasonable time. Thus in this study, a solution to this problem in a reasonable time is obtained by using the genetic algorithm method. The advantage of this method is to find the most appropriate solution by trying possible solutions with a certain number of populations. Results : Different population sizes are considered in the study. 1000 iterations are made for each population. According to the genetic algorithm results, the best result is obtained in the lowest population size. The total distance has been shortened by about 14% with this method. Besides, the number of vehicles in each region and which vehicle will serve to whom has also been determined. This study, which is a real-life application, has provided serious profitability to the food company even from this region alone. Besides, there have been improvements at different rates in each of the seven regions. Customers' ability to receive service at any time has maximized customer satisfaction and increased the ability to work in the long term. Conclusions: The method and results used in the study were positive for the food company. However, the metaheuristic algorithm used in this study does not guarantee an optimal result. Therefore, mathematical models or simulation models can be considered in terms of future studies. Besides, in addition to the time windows problem, the pickup problem can also be taken into account and different solution proposals can be developed.

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.