Citation
Ant Colony Optimization Approaches for Scheduling Jobs with Incompatible Families on Parallel Batch Machines. Proceedings of the 4th Multidisciplinary International Scheduling Conference: Theory and Applications (MISTA 2009), 10-12 Aug 2009, Dublin, Ireland, pages 105-114, 2009.
Paper
Abstract
In this paper, we suggest an Ant Colony System (ACS) to solve a scheduling problem for jobs with incompatible families on parallel batch machines. We are interested in minimizing total weighted tardiness (TWT) of the jobs. Problems of this type have practical importance in semiconductor manufacturing. The ACS scheme includes an efficient local search technique based on swapping jobs across different batches of the same family. A comparison of the suggested ACS scheme with a dispatching rule based approach and a genetic algorithm (GA) from previous research is performed based on stochastically generated test instances. It turns out that the ACS approach slightly outperforms the GA with respect to solution quality but it provides the results using considerably less computational time. We describe extensive computational experimentation to find appropriate parameters for the ACS scheme. Finally, we also present a MAX-MIN Ant System (MMAS) and compare its performance with the ACS approach. MMAS provides basically the same solution quality, but it requires much more computational efforts.
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Bibtex
@INPROCEEDINGS{2009-105-114-P, author = {L. Monch and C. Almeder},
title = {Ant Colony Optimization Approaches for Scheduling Jobs with Incompatible Families on Parallel Batch Machines},
booktitle = {Proceedings of the 4th Multidisciplinary International Scheduling Conference: Theory and Applications (MISTA 2009), 10-12 Aug 2009, Dublin, Ireland},
year = {2009},
editor = {J. Blazewicz and M. Drozdowski and G. Kendall and B. McCollum},
pages = {105--114},
note = {Paper},
abstract = {In this paper, we suggest an Ant Colony System (ACS) to solve a scheduling problem for jobs with incompatible families on parallel batch machines. We are interested in minimizing total weighted tardiness (TWT) of the jobs. Problems of this type have practical importance in semiconductor manufacturing. The ACS scheme includes an efficient local search technique based on swapping jobs across different batches of the same family. A comparison of the suggested ACS scheme with a dispatching rule based approach and a genetic algorithm (GA) from previous research is performed based on stochastically generated test instances. It turns out that the ACS approach slightly outperforms the GA with respect to solution quality but it provides the results using considerably less computational time. We describe extensive computational experimentation to find appropriate parameters for the ACS scheme. Finally, we also present a MAX-MIN Ant System (MMAS) and compare its performance with the ACS approach. MMAS provides basically the same solution quality, but it requires much more computational efforts.},
owner = {gxk},
timestamp = {2010.10.11},
webpdf = {2009-105-114-P.pdf} }