Flexible flowshop scheduling problem considering manpower skill-based processing times

Document Type : Research Paper


1 Department of Industrial Engineering and Management, Shahrood University of Technology, Shahrood, Iran

2 Department of Industrial Engineering, Sari Branch, Islamic Azad University, Sari, Iran

3 Department of Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran



Scheduling for flexible flowshop environments are generally limited by resources such as manpower and machines. However, the majority of efforts tackle machines as the only constrained resource. This paper aims to investigate the problem of scheduling in flexible flowshop environments considering different skills as human resource constraints to minimize the total completion time. In this way, a mathematical model of complex integer linear programming is presented for solving small-sized problems in a reasonable computational time. In addition, due to the NP-hard nature of the problem, a whale hybrid optimization algorithm is tuned to solve the problem on the large-sized dimensions. In order to evaluate performance of the proposed optimization algorithm, the results are compared with five known optimization algorithms the research background. All evaluations and results show the good performance of the whale hybrid algorithm. Especially, the final solution of the proposed algorithm shows 0.75% deviation of the best solution in solving different instances on the large-scale sizes. However, genetic algorithm, memetic global and local search algorithm, and hybrid salp swarm algorithm are in the next ranks with 3.31, 3.52, and 4.02 percentage respectively. In addition, proper discussions and managerial insights are provided for the relevant managers.


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