An investigation of initial solutions on the performance of an iterated local search algorithm for the permutation flowshop

Ahmed El-Bouri

doi:10.1109/CEC.2012.6256550

An investigation of initial solutions on the performance of an iterated local search algorithm for the permutation flowshop

Ahmed El-Bouri^*

^*Corresponding author for this work

Operations Management & Business Statistics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

6 Citations (Scopus)

Abstract

This paper examines the effect of initial solutions on the performance of an iterated local search (ILS) algorithm for the permutation flowshop problem with the objective of minimizing total flowtime. An ILS algorithm is applied to a set of test problems, and in each separate trial the algorithm is started from an initial solution generated by one of six different methods. Experimental results indicate that initial solutions generated by a neural network are more effective in promoting the performance of the ILS algorithm towards better solutions. A modified version of the ILS algorithm, in which an initially restricted neighborhood search is gradually expanded with each iteration, is also proposed and tested. The results from this modified ILS compare very favorably with published results from a traditional ILS approach.

Original language	English
Title of host publication	2012 IEEE Congress on Evolutionary Computation, CEC 2012
DOIs	https://doi.org/10.1109/CEC.2012.6256550
Publication status	Published - 2012
Event	2012 IEEE Congress on Evolutionary Computation, CEC 2012 - Brisbane, QLD, Australia Duration: Jun 10 2012 → Jun 15 2012

Publication series

Name	2012 IEEE Congress on Evolutionary Computation, CEC 2012

Other

Other	2012 IEEE Congress on Evolutionary Computation, CEC 2012
Country/Territory	Australia
City	Brisbane, QLD
Period	6/10/12 → 6/15/12

Keywords

iterated local search
neural networks
permutation flowshop
total flowtime

ASJC Scopus subject areas

Computational Theory and Mathematics
Theoretical Computer Science

Access to Document

10.1109/CEC.2012.6256550

Cite this

El-Bouri, A 2012, An investigation of initial solutions on the performance of an iterated local search algorithm for the permutation flowshop. in 2012 IEEE Congress on Evolutionary Computation, CEC 2012., 6256550, 2012 IEEE Congress on Evolutionary Computation, CEC 2012, 2012 IEEE Congress on Evolutionary Computation, CEC 2012, Brisbane, QLD, Australia, 6/10/12. https://doi.org/10.1109/CEC.2012.6256550

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abstract = "This paper examines the effect of initial solutions on the performance of an iterated local search (ILS) algorithm for the permutation flowshop problem with the objective of minimizing total flowtime. An ILS algorithm is applied to a set of test problems, and in each separate trial the algorithm is started from an initial solution generated by one of six different methods. Experimental results indicate that initial solutions generated by a neural network are more effective in promoting the performance of the ILS algorithm towards better solutions. A modified version of the ILS algorithm, in which an initially restricted neighborhood search is gradually expanded with each iteration, is also proposed and tested. The results from this modified ILS compare very favorably with published results from a traditional ILS approach.",

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AB - This paper examines the effect of initial solutions on the performance of an iterated local search (ILS) algorithm for the permutation flowshop problem with the objective of minimizing total flowtime. An ILS algorithm is applied to a set of test problems, and in each separate trial the algorithm is started from an initial solution generated by one of six different methods. Experimental results indicate that initial solutions generated by a neural network are more effective in promoting the performance of the ILS algorithm towards better solutions. A modified version of the ILS algorithm, in which an initially restricted neighborhood search is gradually expanded with each iteration, is also proposed and tested. The results from this modified ILS compare very favorably with published results from a traditional ILS approach.

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KW - neural networks

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KW - total flowtime

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An investigation of initial solutions on the performance of an iterated local search algorithm for the permutation flowshop

Abstract

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Keywords

ASJC Scopus subject areas

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