Research On Multi-mode Resource Constrained Project Scheduling Problem Base On Particle Swarm Optimization

Along with the fierce increasingly market competition caused by economic globalization, modern projects tend to be more and more complex, they request shorter time, higher quality and lower cost. The multi-mode resource constrained project scheduling problem (MRCPSP) is a kind of typical project scheduling problems; it belongs to the NP-hard problems. A few scholars solve this problem using heuristic algorithms, such as Genetic Algorithms, Simulated Annealing etc. Particle swarm optimization algorithm is applied to solve the multi-mode resource constraint project problem in this paper; the details of the solution process are introduced.Based on the analyzing of the development of Particle swarm optimization algorithm at home and abroad, Particle Swarm Optimization (PSO) basic theory, the advantages of Particle Swarm Optimization are discussed, and a method that applying PSO to solve multi-mode resource constrained project problem is proposed creatively. The particle speed is defined, and the evolution rules of speed and position are established. A network topology method is designed in order to produce the optimization scheme from the particle. Then considering the specialty of this combinatorial optimization problem and the limit of the standard particle swarm optimization algorithm, an improved particle swarm optimization is presented for improving the optimizing speed and capacity of the algorithm, which is mixed the concepts of variation and Simulated Annealing. At last, the validity of the algorithm is proved by optimizing a complicated MRCPSP problem instance, and this application is realized by designing a system.