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The steam turbine is typically an engineer-to-order product, the assembly of steam turbine is mainly performed by a group of workers. In this paper, we investigate the integrated multi-project scheduling and worker allocation for the assembly of steam turbine. These two problems are interrelated as the tasks durations are not predefined, but depend on the number of workers assigned to that task as well as their skill levels. We develop a mathematical model to represent the problem. In order to solve with the minimization of makespan as the objective, we propose the hybrid algorithm combining particle swarm optimization (PSO) and simulated annealing (SA). The proposed algorithm is tested on the case that uses industrial data from a steam turbine company. The experimental results show that the solution quality of the hybrid algorithm outperform the other three traditional metaheuristic algorithms.

Integrated Multi-project Scheduling and Worker Allocation for the Assembly of Steam Turbines