Parametric analysis for genetic algorithms handling parameters

A General Method for Handling Constraints in Genetic Algorithms

An ecient constraint handling method for genetic algorithms

Many real-world search and optimization problems involve inequality and/or equality constraints and are thus posed as constrained optimization problems. In trying to solve constrained optimization problems using genetic algorithms (GAs) or classical optimization methods, penalty function methods have been the most popular approach, because of their simplicity and ease of implementation. However...

An Efficient Constraint Handling Method for Genetic Algorithms

Many real-world search and optimization problems involve inequality and/or equality constraints and are thus posed as constrained optimization problems. In trying to solve constrained optimization problems using genetic algorithms (GAs) or classical optimization methods, penalty function methods have been the most popular approach, because of their simplicity and ease of implementation. However...

A Niched-Penalty Approach for Constraint Handling in Genetic Algorithms

Kalyanmoy Deb and Samir Agrawal Kanpur Genetic Algorithms Laboratory (KanGAL), Department of Mechanical Engineering, Indian Institute of Technology Kanpur, PIN 208 016, India E-mail: deb,samira @iitk.ac.in Abstract Most applications of genetic algorithms (GAs) in handling constraints use a straightforward penalty function method. Such techniques involve penalty parameters which must be set righ...

non-parametric methods in genetic linkage analysis

one of the most important goals for researchers in the clinic is to try to find newer and more effective ways to diagnose and cure the diseases. these clinical advances can create new points of view in other sciences and their combination with basic sciences such as statistics can improve these researches. in statistical genetics, linkage analysis is a way of finding the exact locus of a diseas...