Online ISSN: 2515-8260

Keywords : Genetic algorithm


Optimization Of SLL Of Rectangular Array Antennas Using Enhanced Firefly Algorithm

Bhagya Sri N.K. Kagitha; Venkateswara Rao Nagalla

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 5, Pages 150-159

Firefly Algorithm is a stochastic and meta heuristic approach inspired from nature having a wide range of applications in solving various optimization problems. Firefly Algorithm (FA) suffers from problem of slow convergence speed. This problem can be solved by using modified Firefly algorithm called as Enhanced Firefly Algorithm. By using this algorithm side lobe level of rectangular antenna array can be reduced considerably without appreciable effect on beam width. SLL is most important array pattern parameter because reduced SLL results in minimizing received noise and interference. Low SLL in the radiation pattern of the rectangular antenna array can be achieved by considering phases and amplitudes of the excitation currents of elements of array as variables to be controlled having fixed spacing between the elements. In this paper SLL of symmetric rectangular array antenna is optimized using Enhanced Firefly algorithm (EFA) and its results are compared to the results obtained with Genetic Algorithm.

Economic Load Dispatch Problem Using Butterfly Optimization Algorithm

Subapriya V; Jaichandran R; Kanaga Suba Raja S; Prathyush P; Rahul Kuzhi Parambil; Sreelakshmi S

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 4, Pages 2773-2778

The objective of the economic load dispatch (ELD) problem is to fulfill the requirement of the load by minimum cost using efficient algorithm. Optimization design strategy is better way to solve the problem with more efficiency. In this paper Butterfly optimization technique has been introduce to find efficient solution That emulates nourishment hunt and mating conduct of butteries. Butterflies uses their sense of smell to locate honeydew target or mating partner. The propose solution is contrasted with PSO and genetic algorithm to analyze performance.