Evaluating the Seeding Genetic Algorithm

نویسندگان

  • Ben Leon Meadows
  • Patricia J. Riddle
  • Cameron Skinner
  • Mike Barley
چکیده

In this paper, we present experimental results supporting early work on the Seeding Genetic Algorithm. We evaluate the algorithm’s performance with various parameterisations, making comparisons to the Canonical Genetic Algorithm, and use these as guidelines as we establish reasonable parameters for the seeding algorithm. We discuss how experimental results complement and confirm aspects of the theoretical basis, such as the exclusion of the deleterious mutation operator from the new algorithm. We report on experiments on GA-di cult problems which demonstrate the Seeding Genetic Algorithm’s ability to overcome local optima and systematic deception.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Genetic-Fuzzy Data Envelopment Analysis Model for Evaluating Financial Institutions Relative Productivity in a Fluctuating Economic Market

This paper presents a Genetic Algorithm Fuzzy Data Envelopment Analysis (GA-FDEA) model that caters for optimal selecting of economic indicators for the measurement of relative productivity and performance of financial institutions. Imprecise or uncertain data of financial institutions due to varying monetary policies and market risk were retrieved from Nigeria Stock Exchange Commission and eva...

متن کامل

Performance Analyses on Population Seeding Techniques for Genetic Algorithms

In Genetic Algorithm (GA), the fitness or quality of individual solutions in the initial population plays a significant part in determining the final optimal solution. The traditional GA with random population seeding technique is simple and proficient however the generated population may contain poor fitness individuals, which take long time to converge to the optimal solution. On the other ha...

متن کامل

Optimization of e-Learning Model Using Fuzzy Genetic Algorithm

E-learning model is examined of three major dimensions. And each dimension has a range of indicators that is effective in optimization and modeling, in many optimization problems in the modeling, target function or constraints may change over time that as a result optimization of these problems can also be changed. If any of these undetermined events be considered in the optimization process, t...

متن کامل

Effective EV Population Initialization Technique for Genetic Algorithm

In traditional Genetic Algorithm, random population seeding technique is simple and efficient however the population may contain poor quality individuals which take long time to converge optimal solution. This motivates to design a population initialization technique with the features of randomness, individual diversity and good quality. In this paper, an initial work has been carried out to de...

متن کامل

Using the Imperialistic Competitive Algorithm Model in Bankruptcy Prediction and Comparison with Genetic Algorithm Model in Listed Companies of Tehran Stock Exchange

Bankruptcy prediction is a major issue in classification of companies. Since bankruptcy is extremely costly, investors, owners, managers, creditors, and government agencies are interested in evaluating the financial status of companies. This study tried to predict bankruptcy among companies registered in Tehran Stock Exchange (Iran) by designing imperialist competitive algorithm and genetic alg...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2013