雜志介紹

Evolutionary Computation雜志介紹

《Evolutionary Computation》是一本以English為主的未開放獲取國際優(yōu)秀期刊，中文名稱進(jìn)化計(jì)算，本刊主要出版、報(bào)道計(jì)算機(jī)科學(xué)-COMPUTER SCIENCE, THEORY & METHODS領(lǐng)域的研究動(dòng)態(tài)以及在該領(lǐng)域取得的各方面的經(jīng)驗(yàn)和科研成果，介紹該領(lǐng)域有關(guān)本專業(yè)的最新進(jìn)展，探討行業(yè)發(fā)展的思路和方法，以促進(jìn)學(xué)術(shù)信息交流，提高行業(yè)發(fā)展。該刊已被國際權(quán)威數(shù)據(jù)庫SCIE收錄，為該領(lǐng)域相關(guān)學(xué)科的發(fā)展起到了良好的推動(dòng)作用，也得到了本專業(yè)人員的廣泛認(rèn)可。該刊最新影響因子為4.6，最新CiteScore 指數(shù)為6.4。

本刊近期中國學(xué)者發(fā)表的論文主要有：

• Parameterized Analysis of Multi-objective Evolutionary Algorithms and the Weighted Vertex Cover Problem.

  Author: Pourhassan M¹, Shi F², Neumann F³.

• A Predictive-Reactive Approach with Genetic Programming and Cooperative Co-evolution for Uncertain Capacitated Arc Routing Problem.

  Author: Liu Y¹, Mei Y², Zhang M³, Zhang Z⁴.

• Difficulty Adjustable and Scalable Constrained Multi-objective Test Problem Toolkit.

  Author: Fan Z¹, Li W², Cai X³, Li H⁴, Wei C⁵, Zhang Q⁶, Deb K⁷, Goodman E⁸.

• Scheduling Functions for Position Updating in Population Based Optimization Algorithms

  Author: jeremy.mange

英文介紹

Evolutionary Computation雜志英文介紹

Evolutionary Computation is a leading journal in its field. It provides an international forum for facilitating and enhancing the exchange of information among researchers involved in both the theoretical and practical aspects of computational systems drawing their inspiration from nature, with particular emphasis on evolutionary models of computation such as genetic algorithms, evolutionary strategies, classifier systems, evolutionary programming, and genetic programming. It welcomes articles from related fields such as swarm intelligence (e.g. Ant Colony Optimization and Particle Swarm Optimization), and other nature-inspired computation paradigms (e.g. Artificial Immune Systems). As well as publishing articles describing theoretical and/or experimental work, the journal also welcomes application-focused papers describing breakthrough results in an application domain or methodological papers where the specificities of the real-world problem led to significant algorithmic improvements that could possibly be generalized to other areas.