1. Solving Traveling Salesman Problem based on Biogeography-based Optimization and Edge Assembly Cross-over

A. Salehi; B. Masoumi

Volume 8, Issue 3 , Summer 2020, , Pages 313-329

http://dx.doi.org/10.22044/jadm.2020.7835.1922

Abstract
  Biogeography-Based Optimization (BBO) algorithm has recently been of great interest to researchers for simplicity of implementation, efficiency, and the low number of parameters. The BBO Algorithm in optimization problems is one of the new algorithms which have been developed based on the biogeography ...  Read More

H.3.15.3. Evolutionary computing and genetic algorithms
2. A Hybrid MOEA/D-TS for Solving Multi-Objective Problems

Sh. Lotfi; F. Karimi

Volume 5, Issue 2 , Summer 2017, , Pages 183-195

http://dx.doi.org/10.22044/jadm.2017.886

Abstract
  In many real-world applications, various optimization problems with conflicting objectives are very common. In this paper we employ Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D), a newly developed method, beside Tabu Search (TS) accompaniment to achieve a new manner for solving ...  Read More

3. Estimation of LPC coefficients using Evolutionary Algorithms

Hossein Marvi; Zeynab Esmaileyan; Ali Harimi

Volume 1, Issue 2 , Summer 2013, , Pages 111-118

http://dx.doi.org/10.22044/jadm.2013.115

Abstract
  The vast use of Linear Prediction Coefficients (LPC) in speech processing systems has intensified the importance of their accurate computation. This paper is concerned with computing LPC coefficients using evolutionary algorithms: Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Dif-ferential ...  Read More