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December 22, 2025

Bio-Inspired Computational Models for Multi-Objective Optimization in Complex Engineering Systems

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Authors

MBMohammed Wasim BhattIndian Institute of Technology JammuRJRubal JeetChandigarh University

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Overview

Hybrid optimization model improves Pareto front diversity and convergence in multi-objective optimization problems.

Key Points

  • To develop a hybrid bio-inspired optimization model for efficient multi-objective optimization.
  • Introduced a hybrid model combining genetic algorithm, particle swarm optimization, and differential evolution.
  • The framework employs adaptive parameter control and integrates various optimization strategies.
  • Tested on six benchmark functions and a real-world welded beam design problem.
  • Achieved an average hypervolume increase of 7.8%.
  • Reduced convergence time by 12.5% on average.
  • Improved spread diversity by 35% compared to existing methods.

Cite This Study

Bhatt et al. (2025) studied this question.

synapsesocial.com/papers/69488bc877063b71e748cdb8https://doi.org/10.63503/j.ijcma.2025.171
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