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Genetic Algorithm in Process Optimisation Problems

  • Victor Oduguwa
  • Ashutosh Tiwari
  • Rajkumar Roy
Part of the Advances in Soft Computing book series (AINSC, volume 32)

Abstract

Genetic Algorithm (GA) is generating considerable interest for solving industrial optimisation problems. It is proving robust in delivering global optimal solutions and helping to resolve limitations encountered in traditional methods. However there are fewer GA applications in the process optimisation. This paper presents an overview of recent GA applications in process optimisation. The paper explores the features of process optimisation and critically evaluates how current GA techniques are suited for such complex problems. The survey outlines the current status and trends of GA applications in process related industries. For each industry, the paper describes the general domain problem, common issues, current trends, and the improvements generated by adopting the GA strategy. The paper concludes with an outline of future research directions.

Keywords

Genetic Algorithm Multiobjective Optimisation Assembly Sequence Planning Process Planning Problem Classical Genetic Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Victor Oduguwa
    • 1
  • Ashutosh Tiwari
    • 1
  • Rajkumar Roy
    • 1
  1. 1.Department of Enterprise Integration, School of Industrial and Manufacturing ScienceCranfield UniversityCranfield, BedfordUK

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