制造环境中的当前订单和库存模型:2008 - 2018年回顾

Z. Momeni, A. Azizi
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引用次数: 8

摘要

本文从订单和库存的角度研究了供应链中的问题和因素。本文的扩展审查表明,额外成本是一个组织的生存最重要的因素,并有显著影响公司的竞争力。然而,持有库存、订单接受和功能风险是尚未同时研究的因素。本文的目的是对供应链管理下订单和库存模型中的关键问题和因素进行综述。本文通过从“Science direct”和Scopus数据库中选取的30种相关知名期刊,对近十年来发表的56篇文章进行了筛选和综述。在56篇论文中,《International Journal of Production Economics》以11篇论文排名第一。在这方面,提出了人工神经网络方法(ANN)、蚁群算法和队列理论的应用。所有发表的文章按照作者编号、第一作者姓名、发表年份、问题、因素、制造业类型、研究方法和结果发现进行分类。本文的研究结果表明,订单管理和库存控制可以帮助决策者和研究人员解决制造业中的一些问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Current Order and Inventory Models in Manufacturing Environments: A Review from 2008 to 2018
This paper studied on supply chain in terms of order and inventory problems and factors. The extended review of this paper showed that extra costs are the most important factors in the survival of an organization and have a significant impact on company competitiveness. However, holding inventory, order acceptance, and functional risks are factors that have not been studied simultaneously. The purpose of this paper is to provide a review on critical problems and factors in order and inventory models under supply chain management. This paper selected and reviewed 56 published articles in a decade through 30 famous relevant journals which were chosen from the “Science direct and Scopus” databases. Amongst 56 articles, “International Journal of Production Economics” was ranked as the first by 11 published articles. In this regard, the applications of the Artificial Neural Network method which called “ANN”, ant colony algorithm and queue theory have been proposed. All published articles were categorized based on the author number, The first author name, publication year, problems, factors, type of manufacturing industries, research methods and results and findings. Results of this paper acknowledge that order management and inventory control can help decision makers and researchers in solving some problems in manufacturing industries.
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