A Scale-Free Based Memetic Algorithm for Resource-Constrained Project Scheduling Problems

The resource-constrained project scheduling problem RCPSP is a popular problem that has attracted attentions of many researchers with various backgrounds. In this paper, a new memetic algorithm MA based on scale-free networks is proposed for solving RCPSPs, namely SFMA-RCPSPs. In SFMA, the chromosomes are located on a scale-free network. Thus, each chromosome can only communicate with the ones that have connections with it. In the experiments, benchmark problems, namely Patterson, J30 and J60, are used to validate the performance of SFMA. The results show that the SFMA performs well in finding out the best known solutions especially for Patterson and J30 data sets, besides, the average deviations from the best known solutions are small. Therefore, SFMA improves the search speed and effect.

[1]  Jing Liu,et al.  A multiagent genetic algorithm for global numerical optimization , 2004, IEEE Trans. Syst. Man Cybern. Part B.

[2]  Chenggong Zhang,et al.  Scale-free fully informed particle swarm optimization algorithm , 2011, Inf. Sci..

[3]  Jing Liu,et al.  A multiagent evolutionary algorithm for constraint satisfaction problems , 2006, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[4]  Jing Liu,et al.  A Multiagent Evolutionary Algorithm for Combinatorial Optimization Problems , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[5]  Rainer Kolisch,et al.  Experimental investigation of heuristics for resource-constrained project scheduling: An update , 2006, Eur. J. Oper. Res..

[6]  Yew-Soon Ong,et al.  Memetic Computation—Past, Present & Future [Research Frontier] , 2010, IEEE Computational Intelligence Magazine.

[7]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[8]  Concepción Maroto,et al.  A Robust Genetic Algorithm for Resource Allocation in Project Scheduling , 2001, Ann. Oper. Res..

[9]  Zbigniew Michalewicz,et al.  Evolutionary Computation 1 , 2018 .

[10]  A. Barabasi,et al.  Lethality and centrality in protein networks , 2001, Nature.

[11]  Rainer Kolisch,et al.  Characterization and generation of a general class of resource-constrained project scheduling problems , 1995 .

[12]  G. Cecchi,et al.  Scale-free brain functional networks. , 2003, Physical review letters.

[13]  Jan Karel Lenstra,et al.  Scheduling subject to resource constraints: classification and complexity , 1983, Discret. Appl. Math..

[14]  Andy J. Keane,et al.  Meta-Lamarckian learning in memetic algorithms , 2004, IEEE Transactions on Evolutionary Computation.

[15]  Pilar Tormos,et al.  An efficient multi-pass heuristic for project scheduling with constrained resources , 2003 .

[16]  Kevin Kok Wai Wong,et al.  Classification of adaptive memetic algorithms: a comparative study , 2006, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[17]  Michael Schwind,et al.  Scale-free networks , 2006, Wirtschaftsinf..

[18]  Krzysztof Fleszar,et al.  Solving the resource-constrained project scheduling problem by a variable neighbourhood search , 2004, Eur. J. Oper. Res..

[19]  Francisco Ballestín,et al.  Justification and RCPSP: A technique that pays , 2005, Eur. J. Oper. Res..

[20]  Jing Liu,et al.  An organizational coevolutionary algorithm for classification , 2006, IEEE Trans. Evol. Comput..

[21]  María Pilar Tormos,et al.  A Competitive Heuristic Solution Technique for Resource-Constrained Project Scheduling , 2001, Ann. Oper. Res..

[22]  Krzysztof Fleszar,et al.  An evolutionary algorithm for resource-constrained project scheduling , 2002, IEEE Trans. Evol. Comput..

[23]  Joshua D. Knowles,et al.  M-PAES: a memetic algorithm for multiobjective optimization , 2000, Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512).

[24]  Francisco Ballestín,et al.  A hybrid genetic algorithm for the resource-constrained project scheduling problem , 2008, Eur. J. Oper. Res..

[25]  Jing Liu,et al.  Moving Block Sequence and Organizational Evolutionary Algorithm for General Floorplanning With Arbitrarily Shaped Rectilinear Blocks , 2008, IEEE Transactions on Evolutionary Computation.

[26]  A. Barabasi,et al.  Scale-free characteristics of random networks: the topology of the world-wide web , 2000 .