In this paper a non-standard constructive approach is described to solve problems of timetabling, so necessary in every school and university. Genetic Algorithms have been used, but adapting them to the characteristics of the problem under consideration. Hard constrains, feasible timetables, have been considered in the problem formulation, forcing us to define a particular population generation...

Through mechanism analysis of simple genetic algorithm(SGA),every genetic operator can be considered as a linear function. So some disadvantages of SGA may be solved if genetic operators are modified to nonlinear function. According to the above method, nonlinear genetic algorithm(NGA) is introduced. By the analysis of the concept of schema, new schema theorem is proved. The above work establis...

Task scheduling problem is one of the most important steps in using cloud computing environment capabilities. Different experiments show that although having an optimum solution is almost impossible but having a sub-optimal solution using heuristic algorithms seems possible. In this paper three heuristic approaches for task scheduling on cloud environment have been compared with each other. The...

There are exact and heuristic algorithms for solving the MKP. Solution quality and time complexity are two main differences among exact and heuristic algorithms. Solution quality is a measure of how close we are from the optimal point and time complexity is a measure of the required time to reach such point. The purpose of this paper is to report the solution quality obtained from the evaluatio...

The use of genetic algorithms for solving aerospace control system design and optimization problems is investigated. A modified genetic algorithm based on floating point representation of the chromosome and appropriate genetic operators is developed and used to design controller gains for an autonomous airvehicle. The controller design problem is formulated along a classical pattern with requir...