Department of Industrial Engineering, Meybod University, Meybod, Iran
Department of Industrial Engineering, Faculty of Engineering, Meybod University, Meybod, Iran
selecting an efficient project portfolio among available projects is a vital decision for any project manager. The main questions are which projects can have more long-term benefit for manager or organization. Due to the complexity of this field of research, todays so many approaches are developed for project selection. Calculation time and the quality of result are two main criterion that almost all researchers have considerate on them. In this research a new hybrid genetic algorithm with new heuristic mutation and cross over are developed to choosing a good portfolio of available projects Presented algorithm is fast and effective to reach the good result in reasonable time. Finding a good point to start as initial population and using good operator a heuristic mutation and cross over are main points of our algorithm. To check the quality of results we compare developed algorithm with some recent ones in the literature and comparison studies and statistical calculation demonstrate the efficiency of the new genetic algorithm to select a good portfolio.