Fuzzy-Chaotic Variant of the Multiverse Optimizer Algorithm in Benchmark Function Optimization

Amezquita L., Castillo O., Cortes-Antonio P.

4th International Conference on Intelligent and Fuzzy Systems (INFUS), Bornova, Turkey, 19 - 21 July 2022, vol.504, pp.53-63 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 504
  • Doi Number: 10.1007/978-3-031-09173-5_8
  • City: Bornova
  • Country: Turkey
  • Page Numbers: pp.53-63
  • Keywords: Multi-verse optimizer, Fuzzy logic, Optimization, Dynamic parameter, Mamdani, Sugeno, FCMVO, Chaotic maps, Chaos theory, Benchmark
  • Istanbul Technical University Affiliated: No


In this work we present a new variation of the Multiverse Optimizer using Fuzzy logic and chaos theory (FCMVO) for optimization of benchmark mathematical functions. Over this study, we present some variations in Mamdani and Sugeno approximations in conjunction with some of the most used chaotic maps in the literature; like the Logistic map, Chebyshev map and Gauss map. By using chaos theory, we are substituting some of the random parameters for the MVO algorithm, and Fuzzy logic is used for dynamic parameter adaptation to substitute some equations of the MVO algorithm. The main tests for the variations presented are done with 13 benchmark mathematical functions, where we compare the original MVO in these functions, the comparison against a Chaotic MVO with 10 different chaotic maps, and the Fuzzy-Chaotic MVO with the same functions, so we can observe the improvement. In this study, we have the objective to determine if the combination of Fuzzy Logic and Chaos theory have significant improvement over the original MVO or its single variations, so we can proceed to further testing over control problems.