Title: Ant-based job shop scheduling with genetic algorithm for makespan minimisation on identical machines

Authors: S. Kavitha; P. Venkumar

Addresses: Department of Mechanical Engineering, Kalasalingam University, Krishnankoil, Tamilnadu, India ' Department of Mechanical Engineering, Kalasalingam University, Krishnankoil, Tamilnadu, India

Abstract: The ant-based optimisation techniques have been used in various problems and could be used in job shop scheduling. The application of ant-based method in job shop scheduling is to find out the sequence of jobs with low time complexity. A new ant-based job shop scheduling algorithm with genetic algorithm is proposed using support, which generates a scheduling of jobs with low waited time for the processes while scheduling the jobs. The support in the new genetic algorithm is inversely proportional to the time complexity. The genetic algorithm with support function is proposed to find out the path in which all the processes have to service with resources. The proposed algorithm produces optimal scheduling in which all processes have to wait minimum time. The problem is to reduce the waiting time of all the processes.

Keywords: ant colony optimisation; ACO; genetic algorithms; job shop scheduling; makespan minimisation; metaheuristics; swarm intelligence; identical machines.

DOI: 10.1504/IJCAET.2017.083392

International Journal of Computer Aided Engineering and Technology, 2017 Vol.9 No.2, pp.199 - 206

Available online: 19 Jan 2017 *

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