Reliability optimization of series-parallel systems using a genetic algorithm

Abstract

& Conclusions-A problem specific genetic algorithm (GA) is developed and demonstrated to analyze series-parallel systems and to determine the optimal design configuration when there are multiple component choices available for each of several k-out-of-n:G subsystems. The problem is to select components and levels of redundancy to optimize some objective function given system level constraints on reliability, cost and/or weight. Previous formulations of the problem have implicit restrictions concerning the type of redundancy allowed, the number of available component choices and whether mixing of components is allowed. The GA used to analyze this problem is a robust evolutionary optimization search technique with very few restrictions concerning the type or size of the design problem. The solution approach was to solve the dual of a nonlinear optimization problem by using a dynamic penalty function. The GA was demonstrated to perform very well on two types of problems, the redundancy allocation problem originally proposed by Fyffe, Hines and Lee and a second, randomly generated problem with more complex k-out-of-n:G configurations.

Optimization of Redundancy Allocation in Multi Level System under Target Availability

“…, 라그랑즈 승수 (Misra 1972), 유전알고리즘 (Coit and Smith 1996, Coit and Smith 1998, Yun and Kim 2004, 김재윤과 신경석 2004, Yun et al 2007), 시뮬레이티드 어닐링 (Yun et al 2006), 개미집단 알고리 즘 (Zhao et al 2007, Nahas et al 2007 …”

Multi-Objective Approaches to Optimal Testing Resource Allocation in Modular Software Systems

“…Alternatively, evolutionary algorithms are meta-heuristics that possess the strong capability of global search, and are usually not very sensitive to initial solutions. Their effectiveness has been demonstrated on a large spectrum of problems in the reliability optimization field, such as resource management and task partition in grid systems [19]- [21], redundancy allocation [22], [23], reliability optimization of weighted voting systems [24], and OTRAPs [7]- [12], [15], [17], [18]. In particular, evolutionary algorithms have been reported to perform better than some other techniques on OTRAPs [7], [9]- [12], [15], [17], [18].…”

Exact cost minimization of a series-parallel reliable system with multiple component choices using an algebraic method

“…Those works use essentially dynamic programming [21], branch and bound methods [12], or Lagrangian relaxation [16], among other techniques. On the contrary, in the literature there are many heuristics and metaheuristic algorithms, such as those based on Genetic Algorithms [7], Tabu Search [15] or Ant Colony Optimization [2], among others.…”