IAs based approach for reliability redundancy allocation problems

Improved Bat Algorithm for Reliability-Redundancy Allocation Problems

“…[27], Hikita etc. [28], Chen [6], Hsieh [29] and Valian [18] are 0.9275, 0.931677, 0.931363, 0.931678,0.931682340 and 0.931682387 respectively. The best result of the proposed IBA is better than the best results obtained by the above six algorithms.…”

“…[24], Chen [6], Coelho [7], Hsieh [29] and kanagaraj [21] are 0.99961, 0.999468, 0.999942, 0.999953 ,0.999954675 and 0.999954675 respectively. The best solution of the proposed has got the better solution than the above six algorithms.…”

“…[28], Hsieh etc. [5], Chen [6], Hsieh [29] and Valian [18] are 0.99996875, 0.99997418, 0.99997658,0.999976649 and 0.999976649 respectively. The best solution of the proposed IBA is better than the best results of above five algorithms, the corresponding improvements were 25.28%, 9.5662%, 0.2989%, 0.0043% and 0.0043% respectively.…”

“…A wide variety of meta-heuristic algorithms emerge. At present, the main metaheuristic algorithms for this problem are: genetic algorithm(GA) [2,3,4,5] immune algorithm(IA) [6,29], variable neighborhood search(VNS) [8], particle swarm optimization(PSO) [9,10,11,19], harmony search(HS) [12,13], ant colony optimization(ACO) [14], Tabu Search(TS) [15], imperialist competitive algorithm(ICA) [16]，improved cuckoo search(ICS) algorithm [18] et al Recently, some researchers have proposed hybrid meta-heuristic algorithms by combining with two kinds of meta-heuristic methods to solve the reliability-redundancy allocation problem. Safaei et al [17] proposed particle swarm optimization algorithm based on simulated annealing (APSO).…”

Multi-criteria reliability optimization for a complex system with a bridge structure in a fuzzy environment: A fuzzy multi-criteria genetic algorithm approach

“…Membership functions such as Generalized Bell, Gaussian, Triangular and Trapezoidal can represent the fuzzy membership [31]. Linear membership functions can provide good quality solutions with much ease, including the widely recommended triangular and trapezoidal membership functions [6,8,11,30,31]. Thus, we use linear functions to define fuzzy memberships of objective functions (or decision criteria).…”