Abstract: Based on a class of actual production decision requirements, a resource investment scheduling problem that depends on project splitting is proposed. Based on the analysis of project splitting's impact on resource investment, the integrated optimization model of project splitting and resource investment scheduling problem is established with the aim of minimizing resource investment. A two-stage integrated optimization algorithm is proposed including project splitting optimization and resource investment scheduling optimization. The feasibility of split conditions is studied in the project splitting stage. Using an initial split and a local adjustment method, a project split program can be quickly obtained. Genetic algorithm with job priority and resource capacity dual list are used for the search frame in the resource investment scheduling stage. With full use of the information in the iterative process, a resource allocation method based on probability distribution is designed to accelerate the algorithm convergence. Results from numerical experiments using PSPLIB standard library prove the effectiveness and reliability of the algorithm.

Key words: project splitting, resource investment, integrated optimization, genetic algorithm