Modeling resource-constrained project scheduling problem and its solution by genetic algorithm

The optimization of the resource-constrained project scheduling is an NP-hard problem. Complexity of the algorithm for solving this problem increases exponentially with the increase of resource constraints. Therefore, traditional optimization methods based on Excel tables cannot calculate the efficient allocation of resources, which will affect the scheduling of project management resources. The optimization problem like multiple resource-constrained project scheduling demands an optimization method based on genetic algorithm, which adopts the decimal encoding based on activity priority combined with the storage of the adjacency matrix in order to effectively solve unauthorized phenomenon in activity scheduling. It also adopts preemption mode of allocation of resources in activities to avoid conflict in resource allocation. Besides, we designs C language program that realizes heuristic genetic algorithm, which can find out the most excellent duration that meets the resource constraints through multiple iterations. Finally, the practical results indicate that genetic algorithm can quickly and efficiently solve this problem.