Cost-Efficient Project Management Based on Distributed Processing Model

In the paper a resource-constrained project scheduling problem (RCPSP) aiming at project cost minimization is investigated. RCPSP is a well-known NP-hard optimization problem. A metaheuristic algorithm was adopted to solve the problem when applied to Critical Chain Project Management (CCPM). It starts with the initial schedule and searches for the cheapest solution satisfying given time constraints. A distributed version of the algorithm is proposed to reduce computation time. Independent processes on remote computers (workers) calculate different schedule modifications in the same time and send results back to a server. The server uses multithreading to distribute project data and search parameters to the workers. The number of workers used to achieve the best performance was estimated. The computational results of distributed processing showed high reduction of time needed to obtain the results, in comparison with centralized processing.