Distributed evolutionary algorithms and their models: A survey of the state-of-the-art
The increasing complexity of real-world optimization problems raises new challenges to
evolutionary computation. Responding to these challenges, distributed evolutionary …
evolutionary computation. Responding to these challenges, distributed evolutionary …
Population topologies for particle swarm optimization and differential evolution
N Lynn, MZ Ali, PN Suganthan - Swarm and evolutionary computation, 2018 - Elsevier
Over the last few decades, many population-based swarm and evolutionary algorithms were
introduced in the literature. It is well known that population topology or sociometry plays an …
introduced in the literature. It is well known that population topology or sociometry plays an …
Mocell: A cellular genetic algorithm for multiobjective optimization
This paper introduces a new cellular genetic algorithm for solving multiobjective continuous
optimization problems. Our approach is characterized by using an external archive to store …
optimization problems. Our approach is characterized by using an external archive to store …
Introduction to cellular genetic algorithms
E Alba, B Dorronsoro - Cellular Genetic Algorithms, 2008 - Springer
Research in exact algorithms, heuristics and metaheuristics for solving combinatorial
optimization problems is nowadays highly on the rise. The main advantage of using exact …
optimization problems is nowadays highly on the rise. The main advantage of using exact …
CCSA: Cellular Crow Search Algorithm with topological neighborhood shapes for optimization
In evolutionary computation, systematically structuring the population is used to manage the
evolution process. Thus controlling the amount of diversity during the algorithm search …
evolution process. Thus controlling the amount of diversity during the algorithm search …
Design issues in a multiobjective cellular genetic algorithm
In this paper we study a number of issues related to the design of a cellular genetic
algorithm (cGA) for multiobjective optimization. We take as an starting point an algorithm …
algorithm (cGA) for multiobjective optimization. We take as an starting point an algorithm …
A better understanding on traffic light scheduling: New cellular GAs and new in-depth analysis of solutions
Vehicle traffic congestion is an increasing concern in metropolitan areas, with negative
implications for health, environment, and economy. Researchers, city managers, and …
implications for health, environment, and economy. Researchers, city managers, and …
Efficient batch job scheduling in grids using cellular memetic algorithms
Due to the complex nature of Grid systems, the design of efficient Grid schedulers is
challenging since such schedulers have to be able to optimize many conflicting criteria in …
challenging since such schedulers have to be able to optimize many conflicting criteria in …
[PDF][PDF] 一种具有演化规则的元胞遗传算法
鲁宇明, 黎明, 李凌 - 电子学报, 2010 - ejournal.org.cn
本文根据元胞个体密度与分布的演化规则, 考虑整个空间元胞个体动态的相互作用,
从更为真实模拟自然界的角度出发, 提出了具有演化规则的元胞遗传算法《 CEGA》 …
从更为真实模拟自然界的角度出发, 提出了具有演化规则的元胞遗传算法《 CEGA》 …
Enhancing gene expression programming based on space partition and jump for symbolic regression
When solving a symbolic regression problem, the gene expression programming (GEP)
algorithm could fall into a premature convergence which terminates the optimization process …
algorithm could fall into a premature convergence which terminates the optimization process …