Using Evolving Algorithm with Distance Indicator for Solving Different Non-linear Optimization Problems

Authors

  • Saja Ayad Department of Mathematics, University of Baghdad, Baghdad, IRAQ.
  • Iraq T. Abbas Department of Mathematics, University of Baghdad, Baghdad, IRAQ.

DOI:

https://doi.org/10.23851/mjs.v33i3.1167

Keywords:

Many Objective Problems, Bat Algorithm, Inverted Generational Distance.

Abstract

In this paper, we have relied on the dominant control system as an important tool in building the group of leaders because it allows leaders to contain less dense areas, avoid local areas and produce a more compact and diverse Pareto front. Nine standard nonlinear functions yielded this result. MaBAT/R2 appears to be more efficient than MOEAD, NSGAII, MPSOD, and SPEA2. MATLAB was used to generate all the results of the proposed method and other methods in the same field of work.

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Published

2022-09-25

How to Cite

[1]
S. . Ayad and I. T. Abbas, “Using Evolving Algorithm with Distance Indicator for Solving Different Non-linear Optimization Problems”, Al-Mustansiriyah Journal of Science, vol. 33, no. 3, pp. 66–73, Sep. 2022.

Issue

Section

Mathematics