Hybrid Differential Evolution Optimization for No-Wait Flow-Shop Scheduling with Sequence-Dependent Setup Times and Release Dates

In this paper, a hybrid algorithm based on differential evolution (DE), namely HDE, is proposed to minimize the total completion time criterion of the no-wait flow-shop scheduling problem (NFSSP) with sequence-dependent setup times (SDSTs) and release dates (RDs), which is a typical NP-hard combinat...

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Published inAdvanced Intelligent Computing pp. 600 - 611
Main Authors Qian, Bin, Zhou, Hua-Bin, Hu, Rong, Xiang, Feng-Hong
Format Book Chapter
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg
SeriesLecture Notes in Computer Science
Subjects
differential evolution
local search
no-wait flow-shop scheduling
release dates
sequence-dependent setup times
speed-up evaluation
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Abstract In this paper, a hybrid algorithm based on differential evolution (DE), namely HDE, is proposed to minimize the total completion time criterion of the no-wait flow-shop scheduling problem (NFSSP) with sequence-dependent setup times (SDSTs) and release dates (RDs), which is a typical NP-hard combinatorial optimization problem with strong engineering background. Firstly, to make DE suitable for solving flow-shop scheduling problem, a largest-order-value (LOV) rule is used to convert the continuous values of individuals in DE to job permutations. Secondly, a speed-up evaluation method is developed according to the property of the NFSSP with SDSTs and RDs. Thirdly, after the DE-based exploration, a problem-dependent local search is developed to emphasize exploitation. Due to the reasonable balance between DE-based global search and problem-dependent local search as well as the utilization of the speed-up evaluation, the NFSSP with SDSTs and RDs can be solved effectively and efficiently. Simulation results and comparisons demonstrate the superiority of HDE in terms of searching quality, robustness, and efficiency.
AbstractList In this paper, a hybrid algorithm based on differential evolution (DE), namely HDE, is proposed to minimize the total completion time criterion of the no-wait flow-shop scheduling problem (NFSSP) with sequence-dependent setup times (SDSTs) and release dates (RDs), which is a typical NP-hard combinatorial optimization problem with strong engineering background. Firstly, to make DE suitable for solving flow-shop scheduling problem, a largest-order-value (LOV) rule is used to convert the continuous values of individuals in DE to job permutations. Secondly, a speed-up evaluation method is developed according to the property of the NFSSP with SDSTs and RDs. Thirdly, after the DE-based exploration, a problem-dependent local search is developed to emphasize exploitation. Due to the reasonable balance between DE-based global search and problem-dependent local search as well as the utilization of the speed-up evaluation, the NFSSP with SDSTs and RDs can be solved effectively and efficiently. Simulation results and comparisons demonstrate the superiority of HDE in terms of searching quality, robustness, and efficiency.
Author Qian, Bin
Xiang, Feng-Hong
Hu, Rong
Zhou, Hua-Bin
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CitedBy_id crossref_primary_10_1007_s11750_024_00669_9
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ContentType Book Chapter
Copyright Springer-Verlag Berlin Heidelberg 2011
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DOI 10.1007/978-3-642-24728-6_81
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EISBN 3642247288
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Editor Bevilacqua, Vitoantonio
Figueroa, Juan Carlos
Gan, Yong
Huang, De-Shuang
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Snippet In this paper, a hybrid algorithm based on differential evolution (DE), namely HDE, is proposed to minimize the total completion time criterion of the no-wait...
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StartPage 600
SubjectTerms differential evolution
local search
no-wait flow-shop scheduling
release dates
sequence-dependent setup times
speed-up evaluation
Title Hybrid Differential Evolution Optimization for No-Wait Flow-Shop Scheduling with Sequence-Dependent Setup Times and Release Dates
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