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A multi-objective differential evolution algorithm for the distributed hybrid flowshop scheduling problem with deteriorating jobs.

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Title: A multi-objective differential evolution algorithm for the distributed hybrid flowshop scheduling problem with deteriorating jobs.
Authors: Sun, Xingping, Gong, Youcai, Kang, Hongwei, Lei, Wei, Jin, Zhanyao, Li, Zuhui, Shen, Yong, Chen, Qingyi
Source: Engineering Optimization; Nove2025, Vol. 57 Issue 11, p3101-3133, 33p
Subject Terms: SCHEDULING, MULTI-objective optimization, PRODUCTION scheduling, DIFFERENTIAL evolution, TARDINESS, OPTIMIZATION algorithms
Abstract: For longevity in the market, manufacturers must strike a balance between monetary benefits and production capability. This article investigates the distributed hybrid flowshop scheduling problem with deteriorating jobs, with the objective of minimizing the makespan and mean tardiness. A mathematical model for the distributed hybrid flowshop scheduling problem is constructed. To minimize the goals, a multi-objective discrete differential evolution (MODDE) method is put forward. For achieving optimization goals, a two-strategy initialization operation is put forth. A local search strategy tailored to the problem is used to improve the algorithm's exploratory power. The proposed MODDE method is compared with currently well-known multi-objective optimization techniques, demonstrating considerable performance gains. The outcome shows that the above methodology is effective for tackling the distributed hybrid flowshop scheduling problem. [ABSTRACT FROM AUTHOR]
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Database: Complementary Index
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Abstract:For longevity in the market, manufacturers must strike a balance between monetary benefits and production capability. This article investigates the distributed hybrid flowshop scheduling problem with deteriorating jobs, with the objective of minimizing the makespan and mean tardiness. A mathematical model for the distributed hybrid flowshop scheduling problem is constructed. To minimize the goals, a multi-objective discrete differential evolution (MODDE) method is put forward. For achieving optimization goals, a two-strategy initialization operation is put forth. A local search strategy tailored to the problem is used to improve the algorithm's exploratory power. The proposed MODDE method is compared with currently well-known multi-objective optimization techniques, demonstrating considerable performance gains. The outcome shows that the above methodology is effective for tackling the distributed hybrid flowshop scheduling problem. [ABSTRACT FROM AUTHOR]
ISSN:0305215X
DOI:10.1080/0305215X.2024.2425724