A Multi-objective Approach based on Competitive Optimization Algorithm and its Engineering Applications

Y. Sharafi; M. Teshnelab; M. Ahmadieh Khanesar

Volume 9, Issue 4 , November 2021, , Pages 497-514

http://dx.doi.org/10.22044/jadm.2021.10698.2204

Abstract
  A new multi-objective evolutionary optimization algorithm is presented based on the competitive optimization algorithm (COOA) to solve multi-objective optimization problems (MOPs). Based on nature-inspired competition, the competitive optimization algorithm acts between animals such as birds, cats, bees, ...  Read More

H.6.4. Clustering
A Multi-Objective Approach to Fuzzy Clustering using ITLBO Algorithm

P. Shahsamandi Esfahani; A. Saghaei

Volume 5, Issue 2 , July 2017, , Pages 307-317

http://dx.doi.org/10.22044/jadm.2016.784

Abstract
  Data clustering is one of the most important areas of research in data mining and knowledge discovery. Recent research in this area has shown that the best clustering results can be achieved using multi-objective methods. In other words, assuming more than one criterion as objective functions for clustering ...  Read More

H.3. Artificial Intelligence
PSO for multi-objective problems: Criteria for leader selection and uniformity distribution

H. Motameni

Volume 4, Issue 1 , March 2016, , Pages 67-76

http://dx.doi.org/10.5829/idosi.JAIDM.2016.04.01.08

Abstract
  This paper proposes a method to solve multi-objective problems using improved Particle Swarm Optimization. We propose leader particles which guide other particles inside the problem domain. Two techniques are suggested for selection and deletion of such particles to improve the optimal solutions. The ...  Read More