Multi-objective project scheduling based on Pareto sorting and chaos weighting

To consider multiple scheduling objectives of resource-constrained project scheduling problem comprehensively and to obtain a approximate nondominated solutions set of the problems efficiently, a bi-objective scheduling model with renewable resource utilization smoothness and period was developed. A genetic algorithm based on Pareto sorting and multi-objective chaos weighting was proposed, and the double linked list structure was used as chromosome encoding mechanism representing activity execution sequence and execution mode. The populations were initialized by random generation and by determination of execution modes based on activity characteristics, and the crossover and adaptive variation operations were proposed. The degree of fitness was calculated by using Pareto sorting and multi-objective chaos weighting. The strategies for reparation and punishment of infeasible solutions were also designed. Project Scheduling Problem LIBrary (PSPLIB) was used to verify the effectiveness of proposed algorithm.