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ACO Applied to Group Shop Scheduling: A Case Study on Intensification and Diversification

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Ant Algorithms (ANTS 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2463))

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Abstract

We present a MAX-MIN Ant System for the Group Shop Scheduling problem and propose several extensions aiming for a more effective intensification and diversification of the search process. Group Shop Scheduling is a general Shop Scheduling problem covering Job Shop Scheduling and Open Shop Scheduling. In general, in Shop Scheduling problems good solutions are scattered all over the search space. It is widely recognized that for such kind of problems, effective intensification and diversification mechanisms are needed to achieve good results. Our main result shows that a basic MAX-MIN Ant System - and potentially any other Ant Colony Optimization algorithm - can be improved by keeping a number of elite solutions found during the search, and using them to guide the search process.

EDAs are covering several algorithms emerging from the field of Evolutionary Computation.

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Author information

Authors and Affiliations

  1. IRIDIA, Université Libre de Bruxelles, CP 194/6, Av. Franklin D. Roosevelt 50, 1050, Brussels, Belgium

    Christian Blum

Authors
  1. Christian Blum
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Editor information

Editors and Affiliations

  1. IRIDIA, Université de Bruxelles, CP 194/6 Avenue Franklin D. Roosevelt 50, 1050, Brussels, Belgium

    Marco Dorigo , Gianni Di Caro  & Michael Sampels ,  & 

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Blum, C. (2002). ACO Applied to Group Shop Scheduling: A Case Study on Intensification and Diversification. In: Dorigo, M., Di Caro, G., Sampels, M. (eds) Ant Algorithms. ANTS 2002. Lecture Notes in Computer Science, vol 2463. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45724-0_2

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  • DOI: https://doi.org/10.1007/3-540-45724-0_2

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44146-5

  • Online ISBN: 978-3-540-45724-4

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