A HYBRID GENETIC ALGORITHM FOR JOB SHOP SCHEUDULING

Authors

  • PROF. SARVADE KISHORI D. Computer Science and Engineering,SVERI’SCollege Of Engineering Pandharpur ,Pandharpur ,India
  • KALSHETTY Y.R. Assistant Professor Computer Science and Engineering, SVERI’sCollege Of Engineering PandharpurzPandharpur,India

Keywords:

Hybrid genetic algorithm,, Job shop scheduling, crossover

Abstract

Job Shop Problem is a criticalone;to solve such problems genetic operators can be used. Population size must be increased so selection and fitness value needed. In genetic first select chromosome then apply crossover and mutation technique to form next generation.To find thecritical path, a new algorithm to find the critical path from schedule was presented. Furthermore, a local search operator was designed, which can improve the local search ability of GA greatly. Based on all these, a hybrid genetic algorithm was proposed and its convergence was proved. The computer simulations were made on a set of benchmark problems and the results demonstrated the effectiveness of the proposed algorithm.

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Published

2021-03-17

Issue

Vol. 3 No. 6 (2016): IJIERT

Section

Articles

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How to Cite

PROF. SARVADE KISHORI D., & KALSHETTY Y.R. (2021). A HYBRID GENETIC ALGORITHM FOR JOB SHOP SCHEUDULING. International Journal of Innovations in Engineering Research and Technology, 3(6), 1-5. https://repo.ijiert.org/index.php/ijiert/article/view/896