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European Conference on Evolutionary Computation in Combinatorial Optimization

EvoCOP 2018: Evolutionary Computation in Combinatorial Optimization pp 85–100Cite as

Automatic Algorithm Configuration for the Permutation Flow Shop Scheduling Problem Minimizing Total Completion Time

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10782))

Abstract

Automatic algorithm configuration aims to automate the often time-consuming task of designing and evaluating search methods. We address the permutation flow shop scheduling problem minimizing total completion time with a context-free grammar that defines how algorithmic components can be combined to form a full heuristic search method. We implement components from various works from the literature, including several local search procedures. The search space defined by the grammar is explored with a racing-based strategy and the algorithms obtained are compared to the state of the art.

A. Brum—CNPq–Brazil scholarship holder.

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Authors and Affiliations

  1. Instituto de Informática, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil

    Artur Brum & Marcus Ritt

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  1. Artur Brum
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  2. Marcus Ritt
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Correspondence to Artur Brum .

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Editors and Affiliations

  1. University of Lille, Lille, France

    Arnaud Liefooghe

  2. University of Manchester, Manchester, United Kingdom

    Manuel López-Ibáñez

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Brum, A., Ritt, M. (2018). Automatic Algorithm Configuration for the Permutation Flow Shop Scheduling Problem Minimizing Total Completion Time. In: Liefooghe, A., López-Ibáñez, M. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2018. Lecture Notes in Computer Science(), vol 10782. Springer, Cham. https://doi.org/10.1007/978-3-319-77449-7_6

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  • DOI: https://doi.org/10.1007/978-3-319-77449-7_6

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