Genetic Algorithm for Solving Optimal Component Arrangement Problem of Circular Consecutive-K-Out-of-N: F System

Proposal of Simulated Annealing Algorithms for Optimal Arrangement in a Circular Consecutive-k-out-of-n: F System

“…GAkp: (4,3,12,1,7,10,2,8,9,5,6,11) S SAstd: (5,9,8,2,10,7,1,12,3,4,11,6) S SArr: (1,7,10,2,8,9,5,6,11,4,3,12) S (12, 1,7,10,2,8,9,5,6,11,4,3) S by EX. We also obtained the optimal solution Downloaded by [George Mason University] at 04:29 15 June 2016…”

“…For both SAstd and SArr, z the evaluation value of state (arrangement) is system reliability calculated by using Hwang's recursive formula [3] z the initial solution (arrangement) is set to , 2,..., ) n , (1 z we employ Metropolis Criterion as the accept criterion, z the temperature T is updated to D u T when the number of acceptance becomes no less than 3 n u or the number of search becomes no less than 5 n u at the temperature, and z search is carried out until 10 T 10 and the number of consecutive search that can not update the best solution becomes 50 n u or more.…”

“…As the number of components n increases, the computing time becomes intolerably long. Shingyochi and Yamamoto [10] proposed an efficient algorithm that can reduce computing time approximately by a factor of 4n as compared to an exhaustive search. It seems difficult, however, to obtain the optimal solution for large size systems within a reasonable computing time even if this efficient algorithm is used.…”

Comparative Study of Several Simulated Annealing Algorithms for Optimal Arrangement Problems in a Circular Consecutive-k-out-of-n: F System

“…As the number of components n increases, however, the computing time becomes intolerably long. Shingyochi and Yamamoto [9] have proposed an efficient algorithm that can reduce computing time to approximately 1/4n as compared to an exhaustive search. It seems difficult, however, to obtain the optimal solution for large size systems within a reasonable computing time even if this efficient algorithm is used.…”

“…Furthermore, Shingyochi et al [11] have proposed two types of simulated annealing algorithms. Here, simulated annealing (SA) algorithm [4] is one of meta-heuristic algorithms Downloaded by [University of California, San Diego] at 12:48 29 June 2016…”