In MOEAs with elitism, the data structures and algorithms for storing and updating archives may have a great impact on the CPU time, especially when optimizing continuous problems with larger population sizes. In this paper, we introduce Quad-trees as an efficient data structure for storing Pareto-points. Apart from conventional linear lists, we have implemented three kinds of Quad-trees for th...

This paper presents a genetic algorithm for solving the optimal transmission network applied to the expansion planning of Colombia’s system. Main improvements have been introduced in the genetic algorithm: initial population is obtained by constructive heuristic methods of optimization, and elitism and building block concepts are used in the optimization process. An important part of this optim...

In this paper we present a new chromosome representation for evolving digital circuits. The representation is based very closely on the chip architecture of the Xilinx 6216 FPGA. We examine the effectiveness of evolving circuit functionality by using randomly chosen examples taken from the truth table. We consider the merits of a cell architecture in which functional cells alternate with routin...

In this paper, a new genetic approach based on arithmetic crossover for solving the economic dispatch problem is proposed. Elitism, arithmetic crossover and mutation are used in the genetic algorithm to generate successive sets of possible operating policies. The proposed technique improves the quality of the solution. The new genetic approach is compared with an improved Hopfield NN approach (...

−− Dynamic Matrix Control Algorithm is a powerful control method widely applied to industrial processes. The idea of this work is to use the Genetic Algorithms (GA) with the elitism strategy to optimize the tuning parameters of the Dynamic Matrix Controller for SISO (single-input single-output) and MIMO (multi-input multi-output) processes with constraints. A comparison is made between the comp...

In partial shading situations, the power–voltage (P–V) characteristics of photovoltaic (PV) systems become more complex due to many local maxima. Hence, traditional maximum power point tracking (MPPT) techniques fail recognize global (MPP), resulting in a significant drop produced power. Global optimization strategies, such as metaheuristic approaches, efficiently address this issue. This work ...

Among the currently successful Evolutionary Multi-Objective Algorithms (MOEAs), elitism and no sharing factor are two common characteristics and have been demonstrated to improve performance significantly. Based on these two principles, two heuristics, with which impressive improvements were showed in single objective optimization, are introduced in a newly designed EMOA in this paper: multi-pa...

The very subject of giftedness is fraught with contradiction and controversy. On the one hand, we often encounter misunderstanding, envy, and perceived elitism—and on the other, admiration, dependency, and respect. Little wonder that our K–12 education system has not yet determined how best to nurture extraordinary individuals so that they can become extraordinary contributors to society—and fe...

Distance method is a very efficient method to solve multicriteria optimization problems using genetic algorithms. This article propose two modifications to distance method. The first modification is the choice of a selection operator that gives better results than the classical roulette wheel when used with distance method. The second one is the introduction of an original elistist strategy, ca...

In this paper, we present the first proposal to use a cultural algorithm to solve multiobjective optimization problems. Our proposal uses evolutionary programming, Pareto ranking and elitism (i.e., an external population). The approach proposed is validated using several examples taken from the specialized literature. Our results are compared with respect to the NSGA-II, which is an algorithm r...