Results 11 to 20 of about 1,067 (175)

Ockham’s Razor in memetic computing: Three stage optimal memetic exploration [PDF]

Information Sciences, 2012
Memetic Computing is a subject in computer science which considers complex structures as the combination of simple agents, memes, whose evolutionary interactions lead to intelligent structures capable of problem-solving. This paper focuses on Memetic Computing optimization algorithms and proposes a counter-tendency approach for algorithmic design ...
Giovanni Iacca, Ferrante Neri, Ernesto Mininno   +2 more
exaly   +11 more sources

Efficient Memetic Continuous Optimization in Agent-based Computing

Procedia Computer Science, 2016
AbstractThis paper deals with a concept of memetic search in agent-based evolutionary computation. In the presented approach, local search is applied during mutation of an agent. Using memetic algorithms causes increased demand on the computing power as the number of fitness function calls increases, therefore careful planning of the fitness computing (
Wojciech Korczynski, Aleksander Byrski, Marek Kisiel-Dorohinicki   +2 more
exaly   +3 more sources

A Prospective Method for the Dynamic Transformation of Structural Balance in Fully Signed Networks [PDF]

Entropy
Structural balance in fully signed networks, integrating both individual attributes and relationships, represents a critical challenge in social computing; however, its dynamic transformation remains underexplored.
Zhanyong Jiao, Jiarui Fan, Ruochen Zhang, Dinghan Duan   +3 more
doaj   +2 more sources

Quantum-Inspired Distributed Memetic Algorithm [PDF]

Complex System Modeling and Simulation, 2022
This paper proposed a novel distributed memetic evolutionary model, where four modules distributed exploration, intensified exploitation, knowledge transfer, and evolutionary restart are coevolved to maximize their strengths and achieve superior global ...
Guanghui Zhang, Wenjing Ma, Keyi Xing, Lining Xing, Kesheng Wang   +4 more
doaj   +2 more sources

Guest editorial: Memetic Computing in the presence of uncertainties [PDF]

Memetic Computing, 2010
The complexity of fitness landscapes, e.g., in terms of multimodalities and presence of plateaus, typical of many realworld optimization problems coupled with the limitations imposed by the No Free Lunch Theorem, are strong mitigating factors for domain-specific Memetic Computing approaches.
Ferrante Neri, Shengxiang Yang
openaire   +8 more sources

Efficient workflow scheduling using an improved multi-objective memetic algorithm in cloud-edge-end collaborative framework [PDF]

Scientific Reports
With the rapid advancement of large-scale model technologies, AI agent frameworks built on foundation models have become a central focus of artificial-intelligence research.
Guangzhang Cui, Wei Zhang, Weiwei Xu, Hujun Bao   +3 more
doaj   +2 more sources

An analysis on separability for Memetic Computing automatic design

Information Sciences, 2014
This paper proposes a computational prototype for automatic design of optimization algorithms. The proposed scheme makes an analysis of the problem that estimates the degree of separability of the optimization problem. The separability is estimated by computing the Pearson correlation indices between pairs of variables.
Fabio Caraffini, Ferrante Neri, Lorenzo Picinali   +2 more
exaly   +6 more sources

Memetic Computation—Past, Present & Future [Research Frontier [PDF]

IEEE Computational Intelligence Magazine, 2010
Taking a lead from the multi-faceted definitions and roles of the term "meme" in memetics, a plethora of potentially rich memetic computing methodologies, frameworks and operational memeinspired algorithms have been developed with considerable success in several realworld domains in the last two decades.
Yew-Soon Ong, Xianshun Chen, Meng Hiot Lim   +2 more
exaly   +2 more sources

A particle swarm optimization based memetic algorithm for dynamic optimization problems [PDF]

, 2010
Copyright @ Springer Science + Business Media B.V. 2010.Recently, there has been an increasing concern from the evolutionary computation community on dynamic optimization problems since many real-world optimization problems are dynamic.
Wang, H, Yang, S, Wang, Dingwei, Hongfeng Wang, Shengxiang Yang, W. H. Ip, Ip, W. H., Dingwei Wang, Yang, Shengxiang, Wang, Hongfeng, Ip, WH, Wang, D   +11 more
core   +6 more sources

A Memetic Algorithm With Reinforcement Learning for Sociotechnical Production Scheduling

IEEE Access, 2023
The following interdisciplinary article presents a memetic algorithm with deep reinforcement learning (DRL) for solving practically oriented dual resource constrained flexible job shop scheduling problems (DRC-FJSSP).
Felix Grumbach, Nour Eldin Alaa Badr, Pascal Reusch, Sebastian Trojahn   +3 more
doaj   +1 more source