RESEARCH PAPER
A Multi-Objective Strategy for Solving the Redundancy Allocation Problem in Reliable Systems via the NSGA-II Algorithm
1
Hebei Chemical & Pharmaceutical College, China
Submission date: 2025-09-27
Final revision date: 2025-12-09
Acceptance date: 2026-02-19
Online publication date: 2026-03-01
KEYWORDS
Reliability EngineeringRedundancy Assignment ProblemMulti-Objective Evolutionary AlgorithmPareto-Optimal ConfigurationsSolution Clustering Techniques
TOPICS
ABSTRACT
This study proposes a novel Multi-Objective Optimization (MOP) method to tackle the Redundancy Allocation Problem (RAP) in reliable systems using the Non-dominated Sorting Genetic Algorithm II (NSGA-II). The research aims to improve System Reliability (SR) while simultaneously reducing cost, weight, and volume, addressing the inherent trade-offs in system design. NSGA-II generates Pareto-Optimal Solutions (POSs), which are further refined using K-Means Clustering to facilitate decision-making and reduce cognitive load. An illustrative application in avionics systems demonstrates the method’s ability to balance reliability with resource constraints effectively. Results show that clustering POSs simplifies decision-making during optimal configuration design. Overall, this approach enhances both reliability and cost-effectiveness, offering broad potential for safety-critical engineering applications.
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| eISSN: | 2956-3860 |
| ISSN: | 1507-2711 |
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