The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper presents a coevolutionary algorithm named cooperative coevolutionary invasive weed optimization (CCIWO) and investigates its performance for global optimization of functions with numerous local optima and also Nash equilibrium (NE) search for games. Ability of CCIWO for function optimization is tested through a set of common benchmarks of stochastic optimization, and reported results are...
This paper presents a novel discrete population based stochastic optimization algorithm inspired from weed colonization. Its performance in a discrete benchmark, time-cost trade-off (TCT) problem, is evaluated and compared with five other evolutionary algorithms. Also we use our proposed discrete invasive weed optimization (DIWO) algorithm for cooperative multiple task assignment of unmanned aerial...
This paper presents a hybrid optimization algorithm which originates from Invasive Weed Optimization (IWO) and Particle Swarm Optimization (PSO). Based on the novel and distinct qualifications of IWO and PSO, we introduce IWO/PSO algorithm and try to combine their excellent features in this extended algorithm. The efficiency of this algorithm both in the case of speed of convergence and optimality...
A method based on the novel optimization algorithm of Invasive Weed colonization Optimization (IWO) is used to study electricity market dynamics. Dynamics of such a multi agent system is analyzed using aspects both from Game theory and IWO. The method is integrated with a power system simulator to consider all the constraints of a realistic power system to make sure that the results are reliable....
We address the automatic school timetabling problem and propose a solution based on co-evolution. A school timetable is a weekly schedule for all the teachers of the school and allocates class periods to teachers according to some constraints. Genetic algorithm has been previously used as a powerful tool for timetabling problems but the intrinsic complexity of these problems and the usually huge number...
The method of multiple heterogeneous ant colonies with information exchange (MHACIE) is presented in this paper with emphasis on the speed of finding the optimal solution and the corresponding computational complexity. The proposed method which is inspired by biology and psychology has a structure composed of several ant colonies. These colonies participate in solving problems in a concurrently manner...
In this paper, the optimization of power-delay-product (PDP) of a high-speed flip-flop via transistor sizing is presented. The optimization is performed using the genetic algorithm (GA). The flip-flop which is used in this optimization is called modified hybrid latch flip-flop (MHLFF). The genetic algorithm is implemented in MATLAB with the fitness function expressed in terms of the power and the...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.