Solving Redundancy Allocation Problems using Jaya Algorithm

Abstract

Reliability-based design is related to the performance analysis of engineering systems. The redundancy allocation problem is one of the most common problems in the reliability-based design approach. The redundancy allocation problem determines the redundancy level of components in a system to maximize system reliability, subject to several constraints. In recent years, obtaining solutions to reliability-related redundancy allocation problems by means of evolving meta-heuristic algorithms has appealed to researchers due to the several drawbacks of classical mathematical methods. Meta-heuristics have shown the potential of obtaining precise solution in optimization problems and many techniques have been applied in the literature for optimal redundancy allocation. In this paper, a recently developed Jaya optimization algorithm is proposed to be applied for redundancy allocation to maximize system reliability. The Jaya algorithm is a simple, population-based intelligent meta-heuristic algorithm consisting of a single phase and an algorithm-specific parameter-less algorithm. This paper aims to present an application of the Jaya algorithm for searching the optimal solution of two redundancy allocation problems from the literature with nonlinear constraints so that system reliability is maximized. The first problem is the over speed protection system for a gas turbine, whose control system is modelled as a four-stage series system. The objective is to determine the optimal level of redundancy of the valves of the protection system under cost and weight constraints. The second one is the redundancy allocation problem of a five-stage series system with volume, weight, and cost constraints. The results are validated by comparing them with two other meta-heuristics.

Keywords

• reliability based design
• redundancy allocation
• series system
• jaya algorithm
• particle swarm optimization
• teaching learning based optimization