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Improvement of Search Process in Genetic Algorithms: An Application of PCB Assembly Sequencing Problem

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New Optimization Techniques in Engineering

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 141))

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Abstract

The challenge of modeling real-world problems, especially the class of NP-complete problems, is that the solution space is usually very large. It often requires very large time to examine all possible solutions to choose the best one. It is sometimes impossible to find the real optimum solution and we have to be satisfied with a certain pseudo-optimum one. There are many optimization and search methods to obtain the pseudo-optimum solutions. In general, these procedures start by checking some given number of variants, then change the search direction towards the more promising area, and finally pick up the best among the examined ones. In these methods, the key point is on how to guide the search process.

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Authors
  1. Nguyen Van Hop
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  2. Mario T. Tabucanon
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© 2004 Springer-Verlag Berlin Heidelberg

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Van Hop, N., Tabucanon, M.T. (2004). Improvement of Search Process in Genetic Algorithms: An Application of PCB Assembly Sequencing Problem. In: New Optimization Techniques in Engineering. Studies in Fuzziness and Soft Computing, vol 141. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39930-8_14

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  • DOI: https://doi.org/10.1007/978-3-540-39930-8_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-05767-0

  • Online ISBN: 978-3-540-39930-8

  • eBook Packages: Springer Book Archive

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