Probabilistic model building Genetic Algorithm (PMBGA): A survey
نویسنده
چکیده
Probabilistic model building Genetic Algorithm (PMBGA) is a novel concept in the field of evolutionary computation which is motivated by an idea of building a probabilistic model of the population to preserve important building blocks in subsequent generation. Growing number of research is being carried out in this field and different variant of PMBGA s has been purposed. Aim of this paper is to survey currently existing PMBGAs, categorise them according to their used probability model, describe their workflow and analyse their strengths and weakness.
منابع مشابه
Discussion of Search Phases of Probabilistic Model-building Genetic Algorithms
Recently, the PMBGA has been focused and well developed. The PMBGA uses the statistical information about parents to produce children. It has a high searching ability. In this paper, the difference of the search process between the PMBGA and the canonical GA is discussed. Through the numerical experiments, it is described that the canonical GA has three phases in its search process. On the othe...
متن کاملProbabilistic Model Building and Competent Genetic Programming
This paper describes a probabilistic model building genetic programming (PMBGP) developed based on the extended compact genetic algorithm (eCGA). Unlike traditional genetic programming, which use fixed recombination operators, the proposed PMBGA adapts linkages. The proposed algorithms, called the extended compact genetic programming (eCGP) adaptively identifies and exchanges non-overlapping bu...
متن کاملDistributed Probabilistic Model-Building Genetic Algorithm
Algorithms where offsprings (new search points) are generated according to the estimated probability model of the good parents are called the Probabilistic Model-Building Genetic Algorithms (PMBGAs). In this paper, a new model of PMBGA, Distributed PMBGA (DPMBGA), is proposed. In the DPMBGA, the correlation between the design variables is considered by PCA when the offsprings are generated. The...
متن کاملUsing Edge Histogram Models to Solve Permutation Problems with Probabilistic Model-Building Genetic Algorithms
Recently, there has been a growing interest in probabilistic model-building genetic algorithms (PMBGAs), which replace traditional variation operators of genetic and evolutionary algorithms by building and sampling a probabilistic model of promising solutions. In this paper we propose a PMBGA that uses edge histogram based sampling algorithms (EHBSAs) to solve problems with candidate solutions ...
متن کاملA PMBGA to Optimize the Selection of Rules for Job Shop Scheduling Based on the Giffler-Thompson Algorithm
Most existing research on the job shop scheduling problem has been focused on the minimization of makespan i.e., the completion time of the last job . However, in the fiercely competitive market nowadays, delivery punctuality is more important for maintaining a high service reputation. So in this paper, we aim at solving job shop scheduling problems with the total weighted tardiness objective. ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2003