Wireless sensor network a powerful network contains many wireless sensors with limited power resource, data processing, and transmission abilities. Wireless sensor capabilities including computational capacity, radio power, and memory capabilities are much limited. Moreover, to design a hierarchy topology, in addition to energy optimization, find an optimum clusters number and best location of ...

Evolutionary algorithms have been recognized to be suitable for extracting approximate solutions of multi-objective problems because of their capability to evolve a set of non-dominated solutions distributed along the Pareto frontier‎. ‎This paper applies an evolutionary optimization scheme‎, ‎inspired by Multi-objective Invasive Weed Optimization (MOIWO) and Non-dominated Sorting (NS) strategi...

This paper approaches a recent hybrid evolutionary algorithm, called Evolutionary Clustering Search (ECS), that proposes a way of detecting promising areas combining an evolutionary algorithm and a iterative clustering. The search strategy become more aggressive in such detected areas by applying local search. In this paper, we developed a preprocessing phase for the ECS applying a locationallo...

this paper focuses on multi-objective designing of multi-machine thyristor controlled series compensator (tcsc) using strength pareto evolutionary algorithm (spea). the tcsc parameters designing problem is converted to an optimization problem with the multi-objective function including the desired damping factor and the desired damping ratio of the power system modes, which is solved by a spea ...

floorplanning is an important step in physical design of vlsi circuits. it is used to plan the positions of a set of circuit modules on a chip in order to optimize the circuit performance. however, modern floorplanning takes better care of providing extra options to place dedicated modules in the hierarchical designs to align circuit blocks one by one within certain bounding box for helping seq...

This paper presents a novel hybrid evolutionary algorithm that combines Particle Swarm Optimization (PSO) and Simulated Annealing (SA) algorithms. When a local optimal solution is reached with PSO, all particles gather around it, and escaping from this local optima becomes difficult . To avoid premature convergence of PSO, we present a new hybrid evolutionary algorithm, called PSOSA, based on t...

This article presents sequential and parallel metaheuristics to solve the virtual machines subletting problem in cloud systems, which deals with allocating virtual machine requests into prebooked resources from a cloud broker, maximizing the broker profit. Three metaheuristic are studied: Simulated Annealing, Genetic Algorithm, and hybrid Evolutionary Algorithm. The experimental evaluation over...