Real-World Applications of Evolutionary Computing

Volume 1803 of the series Lecture Notes in Computer Science pp 107-116


A Genetic Algorithm with Local Search for Solving Job Problems

  • L W CaiAffiliated withDepartment of Electronic Engineering, Shenzhen University
  • , Q H WuAffiliated withDepartment of Electrical Engineering and Electronics, The University of Liverpool
  • , Z Z YongAffiliated withDepartment of Electronic Engineering, Shenzhen University

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This paper presents a genetic algorithm specially designed for job shop problems. The algorithm has a simple coding scheme and new crossover and mutation operators. A simple local search scheme is incorporated in the algorithm leading to a combined genetic algorithm(CGA). It is evaluated in three famous Muth and Thompson problems (i.e. MT6×6, MT10×10, MT20×5). The simulation study shows that this algorithm possesses high efficiency and is able to find out the optimal solutions for the job shop problems.


Combined genetic algorithm local search job shop scheduling