In this paper, we propose a new genetic algorithm for multi-objective optimization problems. That is called “Neighborhood Cultivation Genetic Algorithm (NCGA)”. NCGA includes the mechanisms of other methods such as SPEA2 and NSGA-II. Moreover, NCGA has the mechanism of neighborhood crossover. Because of the neighborhood crossover, the effective search can be performed and good results can be de...

We apply the NSGA-II algorithm and its controlled elitist version NSGA-IIc for the intensity modulated beam radiotherapy dose optimization problem. We compare the performance of the algorithms with objectives for which deterministic optimization methods provide global optimal solutions. The number of parameters to be optimized can be up to a few thousands and the number of objectives varies fro...

Most multiobjective evolutionary algorithms are based on Pareto dominance for measuring the quality of solutions during their search, among them NSGA-II is well-known. A very few algorithms are based on decomposition and implicitly or explicitly try to optimize aggregations of the objectives. MOEA/D is a very recent such an algorithm. One of the major advantages of MOEA/D is that it is very eas...

An improved harmony search algorithm for constrained multi-objective optimization problems is proposed in this paper. Inspired by Particle Swarm Optimization, an inductor particle is introduced to speed up the convergence rate of the CMOHS. Two populations are adopted to increase the opportunity of finding the optimal solutions. Numerical experiments are divided into two parts: the first one co...

In an emergency situation (e.g., tsunami, chemical spill, fire) it may be necessary to displace people to safer locations. Evacuation plans must be prepared so that these movements are properly organized. Based on the ACO (ant colony optimization) meta-heuristic we design a computational model to optimize a multi-objective path-finding associated to an evacuation planning problem. The results a...

With the development of customization concept, small-batch and multi-variety production will become one major modes, especially for fast-moving consumer goods. However, this mode has two issues: high cost long manufacturing period. To address these issues, study proposes a multi-objective optimization model flexible flow-shop to optimize scheduling, which would maximize efficiency by minimizing...

The following MOEA algorithms are briefly summarized and compared: • NPGA Niched Pareto Genetic Algorithm (1994) – NPGA II (2001) • NSGA Non-dominated Sorting Genetic Algorithm (1994) – NSGA II (2000) • SPEA Strength Pareto Evolutionary Algorithm (1998) – SPEA2 (2001) – SPEA2+ (2004) – ISPEA Immunity SPEA (2003) • PAES Pareto Archived Evolution Strategy (2000) – M-PAES Mimetic PAES (2000) • PES...

In this paper the effects of elitism in the Nondominated Sorting Genetic Algorithm (NSGA) are analyzed. Three different kinds of elitism: standard, clustering and Parks & Miller techniques are investigated using two test problems. For the studied problems, the Parks & Miller mechanism generated the best results. Finally, the NSGA with Parks & Miller elitism was applied to determine the nondomin...

Мета – дослідити вплив селективних середовищ в культурі in vitro на життєздатність і показники росту розвитку рослин-регенератів міжвидових гібридів помідора F1 виділити перспективні генотипи для використання у якості підщеп. Методи. Загальнонаукові, вимірювальні, лабораторні, статистичні. Результати. Визначено додавання поживні середовища факторів 50% ФКР Alternaria solani (некротрофний патоге...