Abstract
Nowadays, managing and allocating resources for projects has become increasingly essential for managers. A critical factor affecting the success of a project is the work assignment plan for workers to optimize the completion time. Current solutions to project scheduling problems have not been thoroughly addressed; thus, in this study, we model the labor assignment process in project production as a scheduling problem. To solve this problem, we use an improved genetic algorithm named GA-RT (Genetic Algorithm with Random Crossover and Negative Tournament Selection) and conduct experiments on the iMOPSE standard dataset. Experimental results show that the proposed GA-RT algorithm can effectively solve the project scheduling problem, achieving better performance compared to existing algorithms.
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