Modeling and optimization of multi-skill resource investment problem considering workload balancing of resources

Multi-skilled workers have become more and more critical for the success of manufacturing companies by improving production efficiency and reducing costs. In this paper, extended the multi-skill resource investment problem with considering workload balancing of resource. The objective of the mathematical model is to minimize the weighted resource usage cost and resource balancing penalty, a genetic algorithm with an improved serial schedule generation scheme and the resource usage adjustment module was proposed. The genetic algorithm was designed to code resource capacity list and activities priority list at the same time. The resource allocation problem was effectively solved by the minimum cost-maximum flow multi-skill resource allocation model, and judged the feasibility of resource requirements at a given time limit and selected the optimal combination of resources as the final objective by the heuristic algorithm. Finally, numerical experiment is carried out by using the modified standard example library PSPLIB, and the effectiveness of the algorithm is verified by comparison with other literature algorithm.