Distributed hybrid flowshop scheduling with consistent sublots under delivery time windows: A penalty lot-assisted iterated greedy algorithm

IF 5 3区计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Egyptian Informatics Journal Pub Date : 2024-11-11 DOI:10.1016/j.eij.2024.100566

Jinli Liu , Yuyan Han , Yuting Wang , Yiping Liu , Biao Zhang

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引用次数: 0

Abstract

Integrating the delivery time windows into the distributed hybrid flow shop scheduling contributes to ensuring the timely delivery of products and enhancing customer satisfaction. In view of this, this study focuses on distributed hybrid flowshop scheduling with consistent sublots under the delivery time windows constraint, denoted as

DH F_{m} | {lot}_{cs} | ε (T W E T / D T W)

. However, there exist some challenges of problem model modeling and algorithmic design for the problem to be addressed. Therefore, we first construct a mixed integer linear programming (MILP) model tailored to

DH F_{m} | {lot}_{cs} | ε (T W E T / D T W)

with the aim of minimizing the total weighted earliness and tardiness (

TWET

). Additionally, we introduce a penalty lot-assisted iterated greedy (

P L_I G_I T I

) and idle time insertion to coincide better with delivery time windows, in which a delivery-time-based multi-rule NEH, an adaptive insertion-based reconstruction based on the changing of the delivery status, a trilaminar penalty lot-assisted local search, and an elitist list-based acceptance criterion are designed to save convergence time and reduce the late deliveries attempts. Lastly, we also introduce a completely new method to generate delivery time windows and create 400 distinct instances. Based on the average results from five runs of 400 instances,

P L_I G_I T I

demonstrates improvements of 59.0 %, 72.3 %, 76.9 %, and 25.5 % compared to

HIGT

DABC

CVND

, and

I G_M R

, respectively. When considering the minimum values from each instance,

P L_I G_I T I

exhibits enhancements of 59.4 %, 71.8 %, 74.9 %, and 25.4 % over

HIGT

DABC

CVND

, and

I G_M R

, respectively, it evident that

P L_I G_I T I

can effectively solve

DH F_{m} | {lot}_{cs} | ε (T W E T / D T W)

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交付时间窗口下具有一致子批次的分布式混合流水车间调度：罚分批次辅助迭代贪婪算法

将交货时间窗口纳入分布式混合流水车间调度有助于确保产品的及时交货和提高客户满意度。有鉴于此，本研究重点关注交货时间窗口约束下具有一致子批次的分布式混合流水车间调度，记为 DHFm|lotcs|εTWET/DTW。然而，该问题在模型建模和算法设计方面还存在一些挑战。因此，我们首先针对 DHFm|lotcs|εTWET/DTW，构建了一个混合整数线性规划（MILP）模型，目的是最小化总加权早到和迟到（TWET）。此外，我们还引入了罚分批次辅助迭代贪婪法（PL_IG_ITI）和空闲时间插入法，以更好地与交付时间窗口相吻合，其中基于交付时间的多规则 NEH、基于交付状态变化的自适应插入重构、三层罚分批次辅助局部搜索和基于精英列表的接受准则都是为了节省收敛时间和减少延迟交付尝试而设计的。最后，我们还引入了一种全新的方法来生成交货时间窗口并创建 400 个不同的实例。根据五次运行 400 个实例的平均结果，PL_IG_ITI 与 HIGT、DABC、CVND 和 IG_MR 相比，分别提高了 59.0%、72.3%、76.9% 和 25.5%。在考虑每个实例的最小值时，PL_IG_ITI 与 HIGT、DABC、CVND 和 IG_MR 相比，分别提高了 59.4 %、71.8 %、74.9 % 和 25.4 %，这表明 PL_IG_ITI 可以有效地求解 DHFm|lotcs|εTWET/DTW。

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来源期刊

Egyptian Informatics Journal Decision Sciences-Management Science and Operations Research

CiteScore

11.10

自引率

1.90%

发文量

审稿时长

110 days

期刊介绍： The Egyptian Informatics Journal is published by the Faculty of Computers and Artificial Intelligence, Cairo University. This Journal provides a forum for the state-of-the-art research and development in the fields of computing, including computer sciences, information technologies, information systems, operations research and decision support. Innovative and not-previously-published work in subjects covered by the Journal is encouraged to be submitted, whether from academic, research or commercial sources.