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Multi-objective formulations are realistic models for many complex engineering optimization problems. In many real-life problems, objectives under consideration conflict with each other, and optimizing a particular solution with respect to a single objective can result in unacceptable results with respect to the other objectives. A reasonable solution to a… (More)

& 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… (More)

Al~raet-Reliability optimization has been studied in the literature for decades, usually using a mathematical programming approach. Because of these solution methodologies, restrictions on the type of allowable design have been made, however heuristic optimization approaches are free of such binding restrictions. One difficulty in applying heuristic… (More)

abstract – A new heuristic is proposed and tested for system reliability optimization. The multiple weighted objective heuristic is based on a transformation of the problem into a multiple objective problem, and then ultimately, transformation into a different single objective problem. The multiple objectives are to simultaneously maximize the reliability… (More)

We apply a genetic algorithm (GA) to optimize a reliability design problem using a neural network as a reliability estimator for calculation of the objective function value during the search. The GA produces the lowest cost option for a required system reliability by selecting the appropriate parts and levels of redundancy. We show that the neural network… (More)

A tabu search meta-heuristic has been developed and successfully demonstrated to provide solutions to the system reliability optimization problem of redundancy allocation. Tabu search is particularly well-suited to this problem and it offers distinct advantages compared to alternative optimization methods. While there are many forms of the problem, the… (More)

A custom genetic algorithm was developed and implemented to solve multiple objective multi-state reliability optimization design problems. Many real-world engineering design problems are multiobjective in nature, and among those, several of them have various levels of system performance ranging from perfectly functioning to completely failed. This… (More)