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

Version 2 2024-06-04, 00:10
Version 1 2015-03-02, 15:59
journal contribution
posted on 2024-06-04, 00:10 authored by Samer HanounSamer Hanoun, Douglas CreightonDouglas Creighton, S Nahavandi
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.

History

Journal

International journal of advanced manufacturing technology

Volume

75

Pagination

1501-1516

Location

London, England

ISSN

0268-3768

eISSN

1433-3015

Language

eng

Publication classification

C Journal article, C1 Refereed article in a scholarly journal

Copyright notice

2014, Springer

Issue

9-12

Publisher

Springer

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