Inventory Space Minimization in Smart Factory by a Designed Grey Wolf Optimizer

Liang-Tu Chen, SiWei Zhang, N. Wu, Yan Qiao, Zhichao Zhong
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Abstract

With severe global competitions, how to control inventory so as to reduce the material storage space plays a pivotal role in reducing the daily cost resulting from the land rental. The goal of this paper is to develop a periodic material delivering schedule to minimize the space required for inventory. We take a leading home appliance manufacturing system in China as a case problem to study the material delivery scheduling optimization problem so as to ensure the synchronization between production and material delivering. The problem can be divided into a number of subproblems with each of them served by a turnover vehicle (TV) and this paper investigates one of its subproblems. With the combinatorial nature, we design a grey wolf optimizer algorithm. Experiments and comparisons are made with existing metaheuristics to validate the proposed algorithm. Results demonstrate the efficiency and effectiveness of the proposed method.
基于灰狼优化器的智能工厂库存空间最小化
在全球竞争日趋激烈的情况下,如何控制库存,减少物料储存空间,对于降低土地租赁带来的日常成本起着举足轻重的作用。本文的目标是制定一个定期的材料交付计划,以尽量减少库存所需的空间。我们以国内领先的家电制造系统为案例问题,研究物料配送调度优化问题,以保证生产与物料配送同步。该问题可划分为若干个子问题,每个子问题都由一个周转车(TV)服务,本文研究了其中的一个子问题。利用组合特性,设计了一种灰狼优化算法。与现有的元启发式算法进行了实验和比较,以验证所提出的算法。结果表明了该方法的有效性和有效性。
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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