Aims and scope
Engineering Optimization is an interdisciplinary journal that serves a vast technical community interested in quantitative computational methods of optimization. It emphasizes their practical applications across engineering disciplines including planning, design, manufacturing, and operational processes. The journal’s policy considers optimization as any formal numerical process aimed at enhancing technical performance and fostering innovation within engineering domains. While its primary focus lies on algorithms for numerical optimization, the journal also encourages submissions utilizing methodologies from operations research, decision support, statistical decision theory, systems theory, logical inference, knowledge-based systems, generative artificial intelligence, machine/deep learning, information theory, quantum computing, quantum information processing, and other cutting-edge techniques relevant to optimization in decision-making processes. For example, within the realm of artificial intelligence, the journal welcomes academic papers that explore how artificial intelligence methodologies enhance numerical optimization algorithms or propose innovative artificial intelligence methods to solve engineering optimization challenges.

Innovation in optimization is a fundamental requirement for all submissions, alongside a strong emphasis on engineering applicability. Engineering Optimization strives to encompass all disciplines within the engineering community, with main focus on environmental, civil, mechanical, manufacturing, aerospace, and industrial engineering. The journal invites papers that explore both theoretical research and practical industrial applications, demonstrating clear advancements in state-of-the-art formal optimization processes through innovative developments.

All submitted manuscripts undergo initial evaluation by the Editors. If deemed suitable for further consideration, they are subjected to peer review by independent, anonymous expert referees. The peer review process is single-blind, and submissions are managed through our Submission Portal.

Engineering Optimization is currently participating in a project to evaluate and improve the effectiveness of our editorial policies, and some authors may receive an additional email during the manuscript evaluation process providing guidance on Open Research practices. If you do not want your manuscript to be included, please let us know by emailing datasharing@tandf.co.uk including your Manuscript ID. Your decision to participate or not will have no impact on the editorial decision regarding your submission.