A Hybrid Estimation of Distribution Algorithm with Random Walk local Search for Multi-mode Resource-Constrained Project Scheduling problems

  IJCTT-book-cover
 
International Journal of ComputerTrends and Technology (IJCTT)          
 
© 2014 by IJCTT Journal
Volume-8 Number-2                          
Year of Publication : 2014
Authors : Omar S. Soliman , Elshimaa A. R. Elgendi
DOI :  10.14445/22312803/IJCTT-V8P111

MLA

Omar S. Soliman , Elshimaa A. R. Elgendi . "A Hybrid Estimation of Distribution Algorithm with Random Walk local Search for Multi-mode Resource-Constrained Project Scheduling problems". International Journal of Computer Trends and Technology (IJCTT) 8(2):57-64, February 2014. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
Multi-mode resource-constrained project scheduling problems (MRCPSPs) are classified as NP-hard problems, in which a task has different execution modes characterized by different resource requirements. Estimation of distribution algorithm (EDA) has shown an effective performance for solving such real-world optimization problems but it fails to find the desired optima. This paper integrates a novel hybrid local search technique with EDA to enhance their local search ability. The new local search is based on delete-then-insert operator and a random walk (DIRW) to enhance exploitation abilities of EDA in the neighborhoods of the search space. The proposed algorithm is capable to explore and exploit the search mechanism in the search space through its outer and inner loops. The proposed algorithm is tested and evaluated using benchmark test problems of the project scheduling problem library PSPLIB. Simulation results of the proposed algorithm are compared with the classical EDA algorithm. The obtained results showed that the effectiveness of the proposed algorithm and outperformed the compared EDA algorithm

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Keywords
Multi-mode resource-constrained project scheduling problems, Estimation of distribution algorithm, Local search, Random walk.