Budgetary and Redundancy Optimisation of Homogeneous Series-Parallel Systems Subject to Availability Constraints Using Matlab Implemented Genetic Computing

Abstract

This paper deals with finding optimal structures and redundant safety designs with minimal costs for series-Parallel multi state system (MSS) configurations subject to availability constraints using genetic algorithms as optimisation mean, since these biologically inspired evolution concepts showed stability, powerfulness, and effectiveness in solving such complex combinatorial optimisation tasks. The routine has been written in Matlab and the tests have been performed using some test data belonging to already existing models (Levitin, Lisnianski, and Ouzineb).

A redundancy strategy for minimizing cost in systems with non-disjoint subsystems under reliability constraint

“…Gago et al (2013) formulated a redundancy allocation problem minimizing the design cost for a series-parallel system with multiple component choices while ensuring a given system reliability level, where they posed the problem as a non-linear integer programming problem. Chaaban et al (2013) considered a problem of finding optimal redundant safety designs with cost minimization for series-parallel systems, where genetic optimization approaches were used to solve the problem. Caserta and Voß (2015) discussed a constrained redundancy allocation problem for series-parallel system configuration where the problem is transformed into a multiple choice knapsack problem and solved to optimality using a branch and cut algorithm.…”