Solving resource-constrained project scheduling problem using metaheuristic algorithm

We propose the metaheuristic algorithm to solve the The Resource-Constrained Project Scheduling Problem (RCPSP). The approach method extends the Particle Swarm Optimization (PSO) by regrouping the agent particles within the appropriate radius of the circle. It initializes the group of particles, calculates the fitness function, and finds the best particle in that group. Then, it incorporates the adaptive mutation and forward-backward improvement to hybridize local search algorithm for constructing the feasible project scheduling with the minimal make-span. The efficiency of the proposed method is tested against the well-known benchmarks. The results show that the proposed method gives better optimum rate and standard deviation than some existing procedures.