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Multi-objective Evolutionary Algorithms for Resource Allocation Problems

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Evolutionary Multi-Criterion Optimization (EMO 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4403))

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Abstract

The inadequacy of classical methods to handle resource allocation problems (RAPs) draw the attention of evolutionary algorithms (EAs) to these problems. The potentialities of EAs are exploited in the present work for handling two such RAPs of quite different natures, namely (1) university class timetabling problem and (2) land-use management problem. In many cases, these problems are over-simplified by ignoring many important aspects, such as different types of constraints and multiple objective functions. In the present work, two EA-based multi-objective optimizers are developed for handling these two problems by considering various aspects that are common to most of their variants. Finally, the similarities between the problems, and also between their solution techniques, are analyzed through the application of the developed optimizers on two real problems.

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Authors and Affiliations

  1. Indian Institute of Technology Kanpur, Kanpur - 208 016, India

    Dilip Datta & Kalyanmoy Deb

  2. Universidade do Algarve, Campus de Gambelas, 8000-117 Faro, Portugal

    Carlos M. Fonseca

Authors
  1. Dilip Datta
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  2. Kalyanmoy Deb
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  3. Carlos M. Fonseca
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Editor information

Shigeru Obayashi Kalyanmoy Deb Carlo Poloni Tomoyuki Hiroyasu Tadahiko Murata

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Datta, D., Deb, K., Fonseca, C.M. (2007). Multi-objective Evolutionary Algorithms for Resource Allocation Problems. In: Obayashi, S., Deb, K., Poloni, C., Hiroyasu, T., Murata, T. (eds) Evolutionary Multi-Criterion Optimization. EMO 2007. Lecture Notes in Computer Science, vol 4403. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70928-2_32

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  • DOI: https://doi.org/10.1007/978-3-540-70928-2_32

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-70927-5

  • Online ISBN: 978-3-540-70928-2

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