System reliability and cost optimization under various scenarios using NSGA-III

Abstract

Nowadays, industrial systems need to be as reliable as possible in order to ensure safety and competitiveness. This paper addresses the reliabilityredundancy allocation problem (RRAP) of an overspeed protection system in a power plant under various scenarios. Previously, this kind of optimization problems were solved using mathematical programming techniques and considered as a single objective optimization problem, however more recently, bio-inspired algorithms are used to solve this type of optimization problem. In the present work, a multi-objective evolutionary optimization algorithm, called the non-dominated sorting genetic algorithm (NSGA-III) is implemented to solve the problem under a set of nonlinear design constraints. The NSGA-III demonstrates its ability to generate a set of nondominated solutions. The results are discussed under various scenarios of minimum allowable reliability