• Title/Summary/Keyword: Real World Tournament Selection

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Efficient Genetic Algorithm for Resource Constrained Project Scheduling Problem (자원 제약이 있는 프로젝트 스케줄링을 위한 효율적인 유전알고리즘)

  • Lee, Sang-Wook
    • The Journal of the Korea Contents Association
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    • v.11 no.6
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    • pp.59-66
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    • 2011
  • Resource constrained project scheduling problem with multiple resource constraints as well as precedence constraints is well-known as one of the NP-hard problem. Since these problems can't be solved by the deterministic method during reasonable time, the heuristics are generally used for getting a sub-optimal during reasonable time. In this paper, we introduce an efficient genetic algorithm for resource constrained project scheduling problem using crossover which is applying schema theory and real world tournament selection strategy. Experimental results showed that the proposed algorithm is superior to conventional algorithm.

Structural damage identification based on modified Cuckoo Search algorithm

  • Xu, H.J.;Liu, J.K.;Lv, Z.R.
    • Structural Engineering and Mechanics
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    • v.58 no.1
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    • pp.163-179
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    • 2016
  • The Cuckoo search (CS) algorithm is a simple and efficient global optimization algorithm and it has been applied to figure out large range of real-world optimization problem. In this paper, a new formula is introduced to the discovering probability process to improve the convergence rate and the Tournament Selection Strategy is adopted to enhance global search ability of the certain algorithm. Then an approach for structural damage identification based on modified Cuckoo search (MCS) is presented. Meanwhile, we take frequency residual error and the modal assurance criterion (MAC) as indexes of damage detection in view of the crack damage, and the MCS algorithm is utilized to identifying the structural damage. A simply supported beam and a 31-bar truss are studied as numerical example to illustrate the correctness and efficiency of the propose method. Besides, a laboratory work is also conducted to further verification. Studies show that, the proposed method can judge the damage location and degree of structures more accurately than its counterpart even under measurement noise, which demonstrates the MCS algorithm has a higher damage diagnosis precision.