Title :
Memetic algorithm for solving resource constrained project scheduling problems
Author :
Ali, Ismail M. ; Elsayed, Saber M. ; Ray, Tapabrata ; Sarker, Ruhul A.
Author_Institution :
School of Engineering and Information Technology, University of New South Wales, Canberra, Australia
Abstract :
Resource constrained project scheduling problem (RCPSP) is considered to be an NP hard problem. Over the last few decades, many different approaches have been developed in order to solve RCPSPs optimally within a reasonable time limit. However, no existing approach is well-accepted in this regard. In this paper, for efficiently solving RCPSPs, a memetic algorithm is proposed. The proposed algorithm incorporates local search techniques and adaptive mutation with a carefully designed genetic algorithm. To judge the performance of the proposed algorithm, we have solved 31 benchmark problems (16 with 30 activities, and 15 problems with 60 activities), and compared the quality of solutions and computational time with other state-of-the-art algorithms. The results show that our proposed algorithm achieved good quality solutions with a significantly lower computational time.
Keywords :
Algorithm design and analysis; Biological cells; Genetic algorithms; Memetics; Scheduling; Sociology; Statistics; Resource constrained project scheduling; genetic algorithm; local search;
Conference_Titel :
Evolutionary Computation (CEC), 2015 IEEE Congress on
Conference_Location :
Sendai, Japan
DOI :
10.1109/CEC.2015.7257231