Hybrid Ant Colony Optimization-Genetics Algorithm to Minimize Makespan Flow Shop Scheduling

  • Authors

    • Jonas Franky R. Panggabean
    2018-03-05
    https://doi.org/10.14419/ijet.v7i2.2.11868
  • Flow shop scheduling, Ant Colony Optimization Algorithm (ACO), Genetics and Hybrids

  • Abstract

    Flow shop scheduling is a scheduling model in which the job to be processed entirely flows in the same product direction / path. In other words, jobs have routing work together. Scheduling problems often arise if there is n jobs to be processed on the machine m, which must be specified which must be done first and how to allocate jobs on the machine to obtain a scheduled production process. In research of Zini, H and ElBernoussi, S. (2016) NEH Heuristic and Stochastic Greedy Heuristic (SG) algorithms. This paper presents modified harmony search (HS) for flow shop scheduling problems with the aim of minimizing the maximum completion time of all jobs (makespan). To validate the proposed algorithm this computational test was performed using a sample dataset of 60 from the Taillard Benchmark. The HS algorithm is compared with two constructive heuristics of the literature namely the NEH heuristic and stochastic greedy heuristic (SG). The experimental results were obtained on average for the dataset size of 20 x 5 to 50 x 10, that the ACO-GA algorithm has a smaller makespan than the other two algorithms, but for large-size datasets the ACO-GA algorithm has a greater makespan of both algorithms with difference of 1.4 units of time.

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  • How to Cite

    Panggabean, J. F. R. (2018). Hybrid Ant Colony Optimization-Genetics Algorithm to Minimize Makespan Flow Shop Scheduling. International Journal of Engineering & Technology, 7(2.2), 40-44. https://doi.org/10.14419/ijet.v7i2.2.11868

    Received date: 2018-04-22

    Accepted date: 2018-04-22

    Published date: 2018-03-05