雜志介紹

Engineering Optimization雜志介紹

《Engineering Optimization》是一本(ben)以English為(wei)主的(de)(de)(de)(de)未開(kai)放獲取(qu)(qu)國際優(you)秀期刊，中文名稱工程(cheng)優(you)化，本(ben)刊主要出版、報道工程(cheng)技術-ENGINEERING, MULTIDISCIPLINARY領域的(de)(de)(de)(de)研究動(dong)(dong)態以及在該領域取(qu)(qu)得(de)的(de)(de)(de)(de)各方面的(de)(de)(de)(de)經(jing)驗(yan)和科(ke)研成(cheng)果(guo)，介紹該領域有關本(ben)專(zhuan)業的(de)(de)(de)(de)最(zui)(zui)新(xin)(xin)進(jin)展(zhan)(zhan)，探討行業發(fa)(fa)展(zhan)(zhan)的(de)(de)(de)(de)思路和方法，以促進(jin)學術信息(xi)交流(liu)，提高行業發(fa)(fa)展(zhan)(zhan)。該刊已被國際權威數據庫SCIE收錄，為(wei)該領域相關學科(ke)的(de)(de)(de)(de)發(fa)(fa)展(zhan)(zhan)起到(dao)了良好(hao)的(de)(de)(de)(de)推動(dong)(dong)作用(yong)，也得(de)到(dao)了本(ben)專(zhuan)業人員的(de)(de)(de)(de)廣泛認可。該刊最(zui)(zui)新(xin)(xin)影響因子(zi)為(wei)2.2，最(zui)(zui)新(xin)(xin)CiteScore 指數為(wei)5.9。

本刊近期(qi)中(zhong)國學(xue)者(zhe)發(fa)表的論文主要有：

• Topology optimization for disc structures with buckling and displacement constraints

  Author: Wang, Weiwei; Ye, Hongling; Li, Zonghan; Sui, Yunkang

• Topology optimization of thermo-hyperelastic structures utilizing inverse motion based form finding

  Author: Sui, Qianqian; Yan, Jun; Fan, Zhirui; Wallin, Mathias; Ristinmaa, Matti; Niu, Bin

• Deep learning of dispersion engineering in two-dimensional phononic crystals

  Author: Miao, Xuan-Bo; Dong, H. W.; Wang, Yue-Sheng

• Auction-based approach to the job-shop problem with parallel batch processing and a machine availability constraint

  Author: Zeng, Chengkuan; Liu, Zixuan; Tang, Jiafu; Fan, Zhi-Ping; Yan, Chongjun

英文介紹

Engineering Optimization雜志英文介紹

Engineering Optimization is an interdisciplinary engineering journal which serves the large technical community concerned with quantitative computational methods of optimization, and their application to engineering planning, design, manufacture and operational processes. The policy of the journal treats optimization as any formalized numerical process for improvement. Algorithms for numerical optimization are therefore mainstream for the journal, but equally welcome are papers which use the methods of operations research, decision support, statistical decision theory, systems theory, logical inference, knowledge-based systems, artificial intelligence, information theory and processing, and all methods which can be used in the quantitative modelling of the decision-making process.

Innovation in optimization is an essential attribute of all papers but engineering applicability is equally vital. Engineering Optimization aims to cover all disciplines within the engineering community though its main focus is in the areas of environmental, civil, mechanical, aerospace and manufacturing engineering. Papers on both research aspects and practical industrial implementations are welcomed.