Parameter Optimization in Genetic Algorithm and Its Impact on Scheduling Solutions

Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 31)

Abstract

Parameter optimization is an ever fresh and less explored research area, which has ample scope for research investigation and to propose novel findings and interpretations. Identification of good parameter values is a highly challenging task which involves tedious and ad hoc course of actions with several heuristic choices. The complexity involved in parameter tweaking is primarily due to the unpredictable and heavily randomized nature of evolutionary algorithmic procedures. In this paper, an attempt was made to tweak the parameters and decision variables of Genetic Algorithm. GA with tweaked parameters was hybridized with Bacterial Foraging Algorithm, and applied to the Job shop and Permutation Flow Shop scheduling problem benchmarks. The results have proven that optimized parameter set tuning has obtained better scheduling performance.

Keywords

Bacterial foraging Genetic algorithm Parameter optimization Job shop scheduling 

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Copyright information

© Springer India 2015

Authors and Affiliations

  1. 1.Department of Computer ApplicationsBharathiar UniversityCoimbatoreIndia
  2. 2.Sri Ramakrishna Engineering CollegeCoimbatoreIndia

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