2022

Journal

Complex & Intelligent Systems, 8(1), 199-212.

This paper studies a single-machine multitasking scheduling problem together with two-agent consideration. The objective
is to look for an optimal schedule to minimize the total tardiness of one agent subject to the total completion time of another
agent has an upper bound. For this problem, a branch-and-bound method equipped with several dominant properties and a
lower bound is exploited to search optimal solutions for small size jobs. Three metaheuristics, cloud simulated annealing
algorithm, genetic algorithm, and simulated annealing algorithm, each with three improvement ways, are proposed to fnd the
near-optimal solutions for large size jobs. The computational studies, experiments, are provided to evaluate the capabilities for
the proposed algorithms. Finally, statistical analysis methods are applied to compare the performances of these algorithms.

@article{wu2022two,
  title={A two-agent one-machine multitasking scheduling problem solving by exact and metaheuristics},
  author={Wu, Chin-Chia and Azzouz, Ameni and Chen, Jia-Yang and Xu, Jianyou and Shen, Wei-Lun and Lu, Lingfa and Ben Said, Lamjed and Lin, Win-Chin},
  journal={Complex \& Intelligent Systems},
  volume={8},
  number={1},
  pages={199--212},
  year={2022},
  publisher={Springer}
}