Multiple Crossover per Couple with Selection of the Two Crossover Operator for Real-Coded Genetic Algorithms
نویسندگان
چکیده
In this paper, we propose a technique for the application of the crossover operator that generates multiple descendants from two parents and selects the two best offspring to replace the parents in the new population. In crossover operator for real-coded genetic algorithms. In particular, we investigate the influence of the number of generated descendants in this operator, the xperimentation that we have carried out, we can observe that it is possible, with multiple descendants, to achieve a suitable balance between the explorative the selection of the two best descendants.
منابع مشابه
Multiple Crossover per Couple with Selection of the Two Best Offspring: An Experimental Study with the BLX-alpha Crossover Operator for Real-Coded Genetic Algorithms
In this paper, we propose a technique for the application of the crossover operator that generates multiple descendants from two parents and selects the two best offspring to replace the parents in the new population. In order to study the proposal, we present different instances based on the BLX-α crossover operator for real-coded genetic algorithms. In particular, we investigate the influence...
متن کاملMulti-Objective Optimization of Solar Thermal Energy Storage Using Hybrid of Particle Swarm Optimization and Multiple Crossover and Mutation Operator
Increasing of net energy storage (Q net) and discharge time of phase change material (t PCM), simultaneously, are important purpose in the design of solar systems. In the present paper, Multi-Objective (MO) based on hybrid of Particle Swarm Optimization (PSO) and multiple crossover and mutation operator is used for Pareto based optimization of solar systems. The conflicting objectives are Q net...
متن کاملDynamic and heuristic fuzzy connectives-based crossover operators for controlling the diversity and convergence of real-coded genetic algorithms
Genetic algorithms are adaptive methods which may be used as approximation heuristic for search and optimization problems. Genetic algorithms process a population of search space solutions with three operations: selection, crossover and mutation. A great problem in the use of genetic algorithms is the premature convergence, a premature stagnation of the search caused by the lack of diversity in...
متن کاملComparison of a Crossover Operator in Binary-coded Genetic Algorithms
Genetic algorithms (GAs) represent a method that mimics the process of natural evolution in effort to find good solutions. In that process, crossover operator plays an important role. To comprehend the genetic algorithms as a whole, it is necessary to understand the role of a crossover operator. Today, there are a number of different crossover operators that can be used in binary-coded GAs. How...
متن کاملA Crossover Operator Using Independent Component Analysis for Real-Coded Genetic Algorithms
For Real-coded Genetic Algorithms, there have been proposed many crossover operators. The blend crossover (BLX-α) proposed by Eshelman and Schaffer shows good search ability for separable fitness functions. However, because of its component-wise operation, the BLX-α faces difficulties in optimization of non-separable fitness functions. The present paper proposes a novel crossover operator that ...
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 2002