《IEEE進(jìn)化計(jì)算匯刊》出版了進(jìn)化計(jì)算和相關(guān)領(lǐng)域的檔案質(zhì)量原著，包括自然啟發(fā)算法、基于人群的方法、選擇和變化為積分的優(yōu)化以及這些范例結(jié)合的混合系統(tǒng)。純理論論文被認(rèn)為是提供對(duì)這些計(jì)算領(lǐng)域的一般性見解的應(yīng)用論文。

IEEE Transactions on Evolutionary Computation publishes archival quality original papers in evolutionary computation and related areas including nature-inspired algorithms, population-based methods, and optimization where selection and variation are integral, and hybrid systems where these paradigms are combined. Purely theoretical papers are considered as are application papers that provide general insights into these areas of computation.