with the rapid development of the internet, the amount of information and data which are produced, are extremely massive. hence, client will be confused with huge amount of data, and it is difficult to understand which ones are useful. data mining can overcome this problem. while data mining is using on cloud computing, it is reducing time of processing, energy usage and costs. as the speed of ...

clustering is one of the known techniques in the field of data mining where data with similar properties is within the set of categories. k-means algorithm is one the simplest clustering algorithms which have disadvantages sensitive to initial values of the clusters and converging to the local optimum. in recent years, several algorithms are provided based on evolutionary algorithms for cluster...

this paper presents a multi-objective resource-constrained project scheduling problem with positive and negative cash flows. the net present value (npv) maximization and making span minimization are this study objectives. and since this problem is considered as complex optimization in np-hard context, we present a mathematical model for the given problem and solve three evolutionary algorithms;...

finding an optimal path for a robot in a soccer field involves different parameters such as the positions of the robot, positions of the obstacles, etc. due to simplicity and smoothness of ferguson spline, it has been employed for path planning between arbitrary points on the field in many research teams. in order to optimize the parameters of ferguson spline some evolutionary or intelligent al...

Many real world problems can be modelled as an optimization problem. Evolutionary algorithms are used to solve these problems. Ant colony algorithm is a class of evolutionary algorithms that have been inspired of some specific ants looking for food in the nature. These ants leave trail pheromone on the ground to mark good ways that can be followed by other members of the group. Ant colony optim...