A discrete artificial bee colony algorithm for the no-idle permutation flowshop scheduling problem with the total tardiness criterion
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Date
2013
Authors
M. Fatih Tasgetiren
Quan-Ke Pan
P. N. Suganthan
Adalet Oner
Journal Title
Journal ISSN
Volume Title
Publisher
ELSEVIER SCIENCE INC
Open Access Color
HYBRID
Green Open Access
Yes
OpenAIRE Downloads
5
OpenAIRE Views
3
Publicly Funded
No
Abstract
In this paper we present a discrete artificial bee colony algorithm to solve the no-idle permutation flowshop scheduling problem with the total tardiness criterion. The no-idle permutation flowshop problem is a variant of the well-known permutation flowshop scheduling problem where idle time is not allowed on machines. In other words the start time of processing the first job on a given machine must be delayed in order to satisfy the no-idle constraint. The paper presents the following contributions: First of all a discrete artificial bee colony algorithm is presented to solve the problem on hand first time in the literature. Secondly some novel methods of calculating the total tardiness from make-span are introduced for the no-idle permutation flowshop scheduling problem. Finally the main contribution of the paper is due to the fact that a novel speed-up method for the insertion neighborhood is developed for the total tardiness criterion. The performance of the discrete artificial bee colony algorithm is evaluated against a traditional genetic algorithm. The computational results show its highly competitive performance when compared to the genetic algorithm. Ultimately we provide the best known solutions for the total tardiness criterion with different due date tightness levels for the first time in the literature for the Taillard's benchmark suit. (C) 2013 Elsevier Inc. All rights reserved.
Description
Keywords
Artificial bee colony algorithm, No-idle permutation flowshop scheduling problem, Metaheuristics, Evolutionary algorithms, Genetic algorithm, MINIMIZE, MACHINE, WAIT, OPTIMIZATION, SHOPS, TIME, Artificial Bee Colony Algorithm, Genetic Algorithm, Metaheuristics, No-Idle Permutation Flowshop Scheduling Problem, Evolutionary Algorithms, no-idle permutation flowshop scheduling problem, metaheuristics, Deterministic scheduling theory in operations research, :Engineering::Electrical and electronic engineering [DRNTU], genetic algorithm, artificial bee colony algorithm, evolutionary algorithms, Approximation methods and heuristics in mathematical programming
Fields of Science
0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology
Citation
WoS Q
Scopus Q

OpenCitations Citation Count
84
Source
Applied Mathematical Modelling
Volume
37
Issue
10-11
Start Page
6758
End Page
6779
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Citations
CrossRef : 84
Scopus : 103
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Mendeley Readers : 61
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