Determination of Pruned Pareto Sets for the Multi-Objective System Redundancy Allocation Problem

Abstract

In this paper, a new methodology is presented to solve multi-objective system redundancy allocation problems. A tabu search meta-heuristic approach is used to initially find the entire Pareto set, and then a Monte-Carlo simulation provides a decision maker with a pruned set of Pareto solutions based on decision maker's predefined objective function preferences. We are aiming to create a bridge between Pareto optimality and single solution approaches