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A hybrid cuckoo search and variable neighborhood descent for single and multiobjective scheduling problems

Hanoun,S, Creighton,D and Nahavandi,S 2014, A hybrid cuckoo search and variable neighborhood descent for single and multiobjective scheduling problems, International journal of advanced manufacturing technology, vol. 75, no. 9-12, pp. 1501-1516, doi: 10.1007/s00170-014-6262-0.

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Title A hybrid cuckoo search and variable neighborhood descent for single and multiobjective scheduling problems
Author(s) Hanoun,SORCID iD for Hanoun,S orcid.org/0000-0002-8697-1515
Creighton,DORCID iD for Creighton,D orcid.org/0000-0002-9217-1231
Nahavandi,S
Journal name International journal of advanced manufacturing technology
Volume number 75
Issue number 9-12
Start page 1501
End page 1516
Publisher Springer
Place of publication London, England
Publication date 2014-12
ISSN 0268-3768
1433-3015
Keyword(s) Cuckoo search (CS)
Meta-heuristics
Scheduling optimization
Science & Technology
Technology
Automation & Control Systems
Engineering, Manufacturing
Engineering
PARTICLE SWARM OPTIMIZATION
WEIGHTED TARDINESS PROBLEM
ONE-MACHINE
ALGORITHM
MINIMIZE
TIME
Summary Cuckoo search (CS) is a relatively new meta-heuristic that has proven its strength in solving continuous optimization problems. This papers applies cuckoo search to the class of sequencing problems by hybridizing it with a variable neighborhood descent local search for enhancing the quality of the obtained solutions. The Lévy flight operator proposed in the original CS is modified to address the discrete nature of scheduling problems. Two well-known problems are used to demonstrate the effectiveness of the proposed hybrid CS approach. The first is the NP-hard single objective problem of minimizing the weighted total tardiness time (Formula presented.) and the second is the multiobjective problem of minimizing the flowtime ¯ and the maximum tardiness Tmaxfor single machine (Formula presented.). For the first problem, computational results show that the hybrid CS is able to find the optimal solutions for all benchmark test instances with 40, 50, and 100 jobs and for most instances with 150, 200, 250, and 300 jobs. For the second problem, the hybrid CS generated solutions on and very close to the exact Pareto fronts of test instances with 10, 20, 30, and 40 jobs. In general, the results reveal that the hybrid CS is an adequate and robust method for tackling single and multiobjective scheduling problems.
Language eng
DOI 10.1007/s00170-014-6262-0
Field of Research 091302 Automation and Control Engineering
Socio Economic Objective 970109 Expanding Knowledge in Engineering
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2014, Springer
Persistent URL http://hdl.handle.net/10536/DRO/DU:30070156

Document type: Journal Article
Collection: Centre for Intelligent Systems Research
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