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Cat and Mouse Based Optimizer: A New Nature-Inspired Optimization Algorithm.

Mohammad Dehghani1, Štěpán Hubálovský2, Pavel Trojovský1

  • 1Department of Mathematics, Faculty of Science, University of Hradec Králové, 500 03 Hradec Králové, Czech Republic.

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Summary
This summary is machine-generated.

A new Cat and Mouse-Based Optimizer (CMBO) algorithm effectively solves complex optimization problems by mimicking predator-prey dynamics. CMBO demonstrates superior performance compared to established algorithms, finding better solutions for diverse objective functions.

Keywords:
cat and mouseoptimizationoptimization problempopulation-basedstochastic

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Area of Science:

  • Computational intelligence
  • Mathematical optimization
  • Nature-inspired algorithms

Background:

  • Optimization problems are prevalent across science and industry.
  • Population-based algorithms are key to solving these problems.
  • Existing algorithms have limitations in efficiency and solution quality.

Purpose of the Study:

  • Introduce a novel nature-inspired optimization algorithm: the Cat and Mouse-Based Optimizer (CMBO).
  • Simulate the predatory-prey interaction between cats and mice for optimization.
  • Evaluate CMBO's effectiveness on a suite of standard objective functions.

Main Methods:

  • Developed the mathematical model and formulation for the Cat and Mouse-Based Optimizer (CMBO).
  • Tested CMBO on unimodal, high-dimensional multimodal, and fixed-dimensional multimodal objective functions.
  • Compared CMBO's performance against nine well-established optimization algorithms (GA, PSO, GSA, TLBO, GWO, WOA, MPA, TSA, TOA).

Main Results:

  • CMBO demonstrated a strong capability in solving diverse optimization problems.
  • The proposed algorithm achieved competitive results, often outperforming other methods.
  • CMBO consistently provided quasi-optimal solutions closer to the global optimum.

Conclusions:

  • The Cat and Mouse-Based Optimizer (CMBO) is a promising new algorithm for tackling complex optimization challenges.
  • CMBO's nature-inspired approach offers a competitive advantage in finding high-quality solutions.
  • Further research can explore CMBO's application in various scientific and real-world optimization domains.