Throughout the history, Genetic Algorithms (GA) have been widely applied to a broad range of combinatorial optimization problems. Its easy applicability to areas such as transport or industry has been one of the reasons for its great success. In this paper, we propose a new Adaptive Multi-Crossover Population Algorithm (AMCPA). This new technique changes the philosophy of the basic genetic algo...

This paper presents the results of an investigation, and optimization of scheduling system in Sohar University (as a case study) using the genetic algorithm (GA). GA techniques are useful for solving real-world scheduling problem such as timetable which is a complex work and usually done manually. This work focuses on scheduling courses timetable to allocate events (time, subject, and lecturer)...

Abstract In order to solve the problems such as poor diversity and convergence ability of offspring population NSGA-II Algorithm in vehicle production scheduling problem, an improved shop algorithm based on is proposed. The NSGA-ii mainly focuses crossover mutation traditional Algorithm, proposes a new self-adaptive Crossover operator. By comparing individual crowding degree with average popula...

The crossover operator has always been regarded as the primary search operator in genetic algorithm (GA) because it exploits the available information from the population about the search space. Moreover, it is one of the components to consider for improving the behavior of the GA. To improve performance of GA multi parent crossover operators have been used. Multi parent crossover operators inv...

airway mucus hypersecretion health effects caused by air pollutants may range from subtle biochemical or physiological signs, such as mildly reduced lung function, to difficult breathing, wheezing, coughing and exacerbation of existing respiratory conditions such as asthma. the aim of this study was measuring the adverse health effects of air pollution on lung function of primary school student...

Based on recent studies by Guy Jumarie [1] which defines probability density of fractional order and fractional moments by using fractional calculus (fractional derivatives and fractional integration), this study expands the concept of probability density of fractional order by defining the fractional probability measure, which leads to a fractional probability theory parallel to the classical ...

Abstract The increase in the size of universities has greatly increased number teachers, students, and courses also difficulty scheduling courses. This study used coevolution to improve genetic algorithm applied it solve course problem universities. Finally, simulation experiments were conducted on traditional improved algorithms MATLAB software. results showed that converged faster produced be...

in this paper, we study wsn design, as a multi-objective optimization problem using ga technique. we study the effects of ga parameters including population size, selection and crossover method and mutation probability on the design. choosing suitable parameters is a trade-off between different network criteria and characteristics. type of deployment, effect of network size, radio communication...

the stochastic outcomes and phenomenon of climate are the reason to use probability sciences in climatology. interactions of most of climatic phenomenon as well as justify them are very acceptable based on probability technique. accordingly it is useful in environmental management and planning. a conditional probability is the probability of an event given that another event has occurred e.g. l...

In this paper we examine the effects of single node mutations on trees evolved via genetic programming. The results show that neutral mutations are less likely for nodes nearer the root and that as evolution proceeds neutral mutations of nodes near the root are progressively less likely. Studies of crossover in tree based GP have shown that when smaller and/or deeper branches are selected for c...