DeepAI AI Chat
Log In Sign Up

A Heuristic Method to Generate Better Initial Population for Evolutionary Methods

06/15/2014
by   Erfan Khaji, et al.
0

Initial population plays an important role in heuristic algorithms such as GA as it help to decrease the time those algorithms need to achieve an acceptable result. Furthermore, it may influence the quality of the final answer given by evolutionary algorithms. In this paper, we shall introduce a heuristic method to generate a target based initial population which possess two mentioned characteristics. The efficiency of the proposed method has been shown by presenting the results of our tests on the benchmarks.

READ FULL TEXT

page 1

page 2

page 3

page 4

02/15/2006

Revisiting Evolutionary Algorithms with On-the-Fly Population Size Adjustment

In an evolutionary algorithm, the population has a very important role a...
03/13/2013

Mixed Strategy May Outperform Pure Strategy: An Initial Study

In pure strategy meta-heuristics, only one search strategy is applied fo...
11/14/2012

A Comparison of Meta-heuristic Search for Interactive Software Design

Advances in processing capacity, coupled with the desire to tackle probl...
10/12/2017

Reduction of Look Up Tables for Computation of Reciprocal of Square Roots

Among many existing algorithms, convergence methods are the most popular...
08/11/2012

A Large Population Size Can Be Unhelpful in Evolutionary Algorithms

The utilization of populations is one of the most important features of ...
07/24/2018

Theoretical Perspective of Convergence Complexity of Evolutionary Algorithms Adopting Optimal Mixing

The optimal mixing evolutionary algorithms (OMEAs) have recently drawn m...