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A Multi-Objective Sine Cosine Algorithm Based on a Competitive Mechanism and Its Application in Engineering Design

Nengxian Liu1, Jeng-Shyang Pan2, Genggeng Liu1

  • 1College of Computer and Data Science, Fuzhou University, Fuzhou 350108, China.

Biomimetics (Basel, Switzerland)
|February 23, 2024
PubMed
Summary
This summary is machine-generated.

A new competitive mechanism multi-objective sine cosine algorithm (CMOSCA) improves convergence and diversity for multi-objective optimization problems (MOPs). This algorithm enhances evolutionary strategies for better real-world engineering design solutions.

Keywords:
competitive mechanismengineering design problemmulti-objective algorithmsine cosine algorithm (SCA)

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Area of Science:

  • Computational Intelligence
  • Optimization Algorithms

Background:

  • Multi-objective optimization problems (MOPs) are prevalent in real-world scenarios.
  • Existing multi-objective evolutionary algorithms (MOEAs) face challenges in balancing convergence and diversity of non-dominated solutions.

Purpose of the Study:

  • To propose an efficient multi-objective sine cosine algorithm with a competitive mechanism (CMOSCA) to address the convergence-diversity trade-off in MOPs.

Main Methods:

  • The CMOSCA utilizes non-dominated sorting and crowding distance for agent ranking and selection.
  • A novel position updating operator is developed using a competitive mechanism based on shift-based density estimation.
  • Outstanding agents guide the evolutionary process, with competition winners integrated into the position update scheme.

Main Results:

  • The CMOSCA demonstrated superior performance on DTLZ, WFG, and ZDT benchmark suites, achieving better convergence and diversity.
  • Statistical results confirmed the CMOSCA's efficiency and effectiveness when applied to engineering design problems.

Conclusions:

  • The proposed CMOSCA effectively balances convergence and diversity for multi-objective optimization.
  • CMOSCA presents a promising approach for solving complex engineering design challenges.