A New Hybrid Algorithm for the Resource Constraint Project Scheduling Problem

In today’s competitive environment, projects must be implemented at a lower cost and in less time, and resources must be used optimally. Therefore, project management and scheduling using an efficient tool is a necessity. Resource constraint project scheduling (RCPSP) is one of the most widely used project planning issues. One of the most difficult non-polynomial problems is that innovative and meta-heuristic methods are more effective than exact solutions. The current study mainly aims to introduce a new meta-innovative algorithm with an imperialist competitive algorithm and genetic algorithm (ICA-GA). By proposing a two-objective project scheduling problem, it is attempted to minimize the project execution time and its cost simultaneously along with a proposed algorithm. Finally, to assess the validity of the ICA-GA hybrid algorithm, the famous MOPSO algorithm in solving the proposed model is utilized. The evaluated data is extracted from the PSPLIB standard library. The study’s results demonstrate that the imperialist-genetic competition algorithm is superior to the MOPSO algorithm and holds high efficiency in solving the proposed model