This paper introduces some results, obtained by experiments with evolutionary algorithms in synthesis of passive LC filters. The aim of the presented experiments was to verify, if heuristic algorithms were able to successfully solve filter design problem including some optimization requirements in the mathematical program environment. As shown in some examples, MAPLE program seems to be a conve...

The influence of non-constant population sizes in evolutionary multi-objective optimization algorithms is investigated. In contrast to evolutionary single-objective optimization algorithms an increasing population size is considered beneficial when approaching the Pareto-front. Firstly, different deterministic schedules are tested, featuring different parameters like the initial population size...

Many experiments have proved that crossover is an essential search operator in evolutionary algorithms, at least for certain functions. However, the rigorous analysis of such algorithms on crossover-friendly functions is still in its infancy. Here a recombinative hill-climber is analyzed on the crossover-friendly function H-IFF introduced by [10]. The dynamics of this algorithm are investigated...

Multi-objective optimization using an evolutionary computation technique is used extensively for solving conflicting multi-objective optimization problems. In this work, an improved strategy of multi-objective differential evolution (MODE) where the mutation strategy is changed to a trigonometric mutation approach is proposed. The proposed strategy along with other well known strategies of MODE...

In this paper, multi-criterion, evolutionary and quantum decision making supported by the Adaptive Quantum-based Multi-criterion Evolutionary Algorithm (AQMEA) has been considered. AQMEA has been developed to the task assignment problem and to underwater vehicle planning. Moreover, the other algorithms like QMEA and QEA have been discussed. Key-Words: quantum algorithms, decision making, multi-...

An overview of evolutionary algorithms is presented covering genetic algorithms, evolution strategies, genetic programming and evolutionary programming. The schema theorem is reviewed and critiqued. Gray codes, bit representations and real-valued representations are discussed for parameter optimization problems. Parallel Island models are also reviewed, and the evaluation of evolutionary algori...

We hypothesize that evolutionary algorithms can effectively schedule coordinated fleets of Earth observing satellites. The constraints are complex and the bottlenecks are not well understood, a condition where evolutionary algorithms are often effective. This is, in part, because evolutionary algorithms require only that one can represent solutions, modify solutions, and evaluate solution fitne...

In this paper a novel method based on evolutionary algorithms is presented to estimate the harmonic components. In general, the optimization of the harmonic estimation process is a multi-component problem, in which evaluation of the phase and harmonic frequency is the nonlinear part of the problem and is solved based on the mathematical and evolutionary methods; while estimation of amplitude of...

The population diversity is an important issue in evolutionary optimization, playing the main role in exploring the search space. The aim of this paper is to analyze the influence of some diversity enhancing mechanisms on the ability of two algorithms related to evolutionary optimization, differential evolution and particle swarm optimization, to solve static and dynamic optimization problems.

Due to the increasing amount of natural disasters such as earthquakes and floods and unnatural disasters such as war and terrorist attacks, Humanitarian Relief Chain (HRC) is taken into consideration of most countries. Besides, this paper aims to contribute humanitarian relief chains under uncertainty. In this paper, we address a humanitarian logistics network design problem including local dis...