A guide for genetic algorithm based on parallel machine scheduling and flexible job-shop scheduling

Ak B., Koc E.

World Conference on Business, Economics and Management (BEM), Antalya, Turkey, 4 - 06 May 2012, vol.62, pp.817-823 identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 62
  • Doi Number: 10.1016/j.sbspro.2012.09.138
  • City: Antalya
  • Country: Turkey
  • Page Numbers: pp.817-823
  • Keywords: Parallel machine scheduling, flexible job shop problem, genetic algorithm, chromosome representation, crossover and mutation operators, REPRESENTATION
  • Ondokuz Mayıs University Affiliated: Yes


Parallel Machine Scheduling (PMS) and Flexible Job-shop Scheduling (FJS) are the hardest combinatorial optimization problems, they require very large scale search space. Solving this kind of combinatorial optimization problems with classical methods are almost impossible or takes considerable long time. Genetic Algorithms (GAs) have shown great advantages in solving combinatorial problems. GAs have the flexibility of set up different chromosome structures in case of distinctive scheduling problems. This paper presents a PMS and FJS chromosome structure, crossover and mutation operator from literature in order to guide for new researchers about scheduling with GAs. (C) 2012 Published by Elsevier Ltd. Selection and/or peer review under responsibility of Prof. Dr. Huseyin Arasli