A discrete artificial bee colony algorithm for the permutation flow shop scheduling problem with total flowtime criterion

Loading...
Publication Logo

Date

2010

Authors

M. Fatih Tasgetiren
Quanke Pan
Ponnuthurai Nagaratnam Suganthan
Angela Hsiang Ling Chen

Journal Title

Journal ISSN

Volume Title

Publisher

Open Access Color

Green Open Access

Yes

OpenAIRE Downloads

OpenAIRE Views

Publicly Funded

No
Impulse
Top 10%
Influence
Top 10%
Popularity
Average

Research Projects

Journal Issue

Abstract

Very recently Jarboui et al. [1] (Computers & Operations Research 36 (2009) 2638-2646) and Tseng and Lin [2] (European Journal of Operational Research 198 (2009) 84-92) presented a novel estimation distribution algorithm (EDA) and a hybrid genetic local search (hGLS) algorithm for the permutation flowshop scheduling (PFSP) with the total flowtime (TFT) criterion respectively. Both algorithms generated excellent results thus improving all the best known solutions reported in the literature so far. However in this paper we present a discrete artificial bee colony (DABC) algorithm hybridized with an iterated greedy (IG) and iterated local search (ILS) algorithms embedded in a variable neighborhood search (VNS) procedure based on swap and insertion neighborhood structures. We also present a hybrid version of our previous discrete differential evolution (hDDE) algorithm employing the IG and VNS structure too. The performance of the DABC and hDDE is highly competitive to the EDA and hGLS algorithms in terms of both solution quality and CPU times. Ultimately 43 out of 60 best known solutions provided very recently by the EDA and hGLS algorithms are further improved by the DABC and hDDE algorithms with short-term search. © 2010 IEEE. © 2011 Elsevier B.V. All rights reserved.

Description

Keywords

Artificial Bee Colonies, Cpu Time, Differential Evolution, Distribution Algorithms, Hybrid Genetic, Iterated Local Search, Neighborhood Structure, Operational Research, Permutation Flow-shop Scheduling, Solution Quality, Total Flowtime, Variable Neighborhood Search, Artificial Intelligence, Biology, Evolutionary Algorithms, Artificial bee colonies, CPU time, Differential Evolution, Distribution algorithms, Hybrid genetic, Iterated local search, Neighborhood structure, Operational research, Permutation flow-shop scheduling, Solution quality, Total flowtime, Variable neighborhood search, Artificial intelligence, Biology, Evolutionary algorithms

Fields of Science

0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Citation

WoS Q

Scopus Q

OpenCitations Logo
OpenCitations Citation Count
15

Source

2010 6th IEEE World Congress on Computational Intelligence WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation CEC 2010

Volume

Issue

Start Page

1

End Page

8
PlumX Metrics
Citations

CrossRef : 10

Scopus : 26

Captures

Mendeley Readers : 32

Google Scholar Logo
Google Scholar™
OpenAlex Logo
OpenAlex FWCI
8.9329

Sustainable Development Goals

SDG data is not available