Open AccessBi-Objective Reliability-Cost Interactive Optimization Model for Series-Parallel System
Author(s) -
Harish Garg
Publication year - 2021
Publication title -
international journal of mathematical, engineering and management sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.228
H-Index - 10
ISSN - 2455-7749
DOI - 10.33889/ijmems.2021.6.5.080
Subject(s) - particle swarm optimization , reliability (semiconductor) , series (stratigraphy) , mathematical optimization , decision maker , computer science , genetic algorithm , moment (physics) , fuzzy logic , vector optimization , multi swarm optimization , operations research , mathematics , artificial intelligence , paleontology , power (physics) , physics , classical mechanics , quantum mechanics , biology
The paper aims are to determine the bi-objective reliability-cost problem of a series-parallel system by employing an interactive approach. Multi-objective optimization is a design methodology that optimizes a combination of objective functions orderly and concurrently. The fuzzy membership functions have been designated to settle the contrary nature of the objectives. Based on these functions and the moment of the objectives in the form of the weight vector, a crisp optimization design is formed. Lastly, the inherited problem is determined with the aid of the PSO (Particle Swarm Optimization) algorithm and confronted with the genetic algorithm. The solution resembling the various choices of the decision-makers towards the evaluation of their decision are listed. A decision-maker can pick an immeasurable one according to his requirement to reach at the aspired goal.