This paper introduces an expanded version of the Invasive Weed Optimization algorithm (exIWO) distinguished by the hybrid strategy of the search space exploration proposed by the authors. The algorithm is evaluated by solving three well-known optimization problems: minimization of numerical functions, feature selection, and the Mona Lisa TSP Challenge as one of the instances of the traveling sa...

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 ...

Linear antenna array design is one of the most important electromagnetic optimization problems of current interest . In the antenna arrays the side lobe level is main problem which causes wastage of energy. This paper describes the application of a recently developed metaheuristic algorithm ,known as the Particle Swarm Optimization Gravitational Search Algorithm(PSOGSA) to optimize the spacing ...

The problem of finding optimal locations of base stations, their pilot powers and channel assignments in UMTS mobile networks belongs to a class of NP-hard problems, and hence, metaheuristics optimization algorithms are widely used for this task. Invasive Weed Optimization (IWO) algorithm is relatively novel and succussed in several real-world applications. Our experiments demonstrate that the ...

An improved Invasive weed optimization (IWO) based on hybrid genetic (HGIWO) is presented. In the new arithmetic, the inertial weight is adaptively adjusted to improve the convergence speed. The weeds are multiples by the selection and hybridization of genetic arithmetic. The import of hybrid genes improves excellent performance of weeds and reduces likelihood on getting into local optimization...

In this paper, Invasive Weed Optimization (IWO) algorithm is used to find the optimum solution of Combined Economic Emission Dispatch (CEED) problem. The main objective is to minimize the fuel cost as well as emission level, while satisfying the power demand and associative operational constraints. The bi-objective problem is made to a single objective function using the price penalty factor. S...