Parameter Tuning of Groceries Scheduling by Genetic Algorithm

  • Authors

    • Mohd Nazmi Noor Shamsuazman
    • Shuzlina Abdul Rahman
    • Nurzeatul Hamimah Abdul Hamid
    2018-12-09
    https://doi.org/10.14419/ijet.v7i4.31.23405
  • Genetic Algorithm, Optimization, Parameter Tuning, Scheduling.

  • Abstract

    Genetic Algorithm (GA) is a promising optimization algorithm that can provide effective solutions to help overcome optimization problems.  However, applying the GA without parameter tuning may result in a low efficiency. Thus, this study investigates the importance of parameter tuning and its applications in solving an optimization problem. The parameter tuning was experimented on groceries scheduling problems to find the shortest time required in delivering the groceries. The experiments were performed on different values of mutation operator, crossover operator and number of iterations on groceries scheduling. The knowledge representation and the architecture of the problem are presented.  The improvements of the search ability are verified by a series of experiments. Our results show that the best mutation operator is the Inversion Mutation, while the best crossover operator is Order 1 Crossover.

     

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  • How to Cite

    Nazmi Noor Shamsuazman, M., Abdul Rahman, S., & Hamimah Abdul Hamid, N. (2018). Parameter Tuning of Groceries Scheduling by Genetic Algorithm. International Journal of Engineering & Technology, 7(4.31), 336-340. https://doi.org/10.14419/ijet.v7i4.31.23405

    Received date: 2018-12-08

    Accepted date: 2018-12-08

    Published date: 2018-12-09