Optimization and Engineering

Aims & Scope

Optimization and Engineering is a multidisciplinary journal; its primary goal is to promote the application of optimization methods in the general area of engineering sciences.

We expect submissions to OPTE not only to make a significant optimization contribution but also to impact a specific engineering application.

Topics of Interest: -Optimization: All methods and algorithms of mathematical optimization, including blackbox and derivative-free optimization, continuous optimization, discrete optimization, global optimization, linear and conic optimization, multiobjective optimization, PDE-constrained optimization & control, and stochastic optimization.

Numerical and implementation issues, optimization software, benchmarking, and case studies. -Engineering Sciences: Aerospace engineering, biomedical engineering, chemical & process engineering, civil, environmental, & architectural engineering, electrical engineering, financial engineering, geosciences, healthcare engineering, industrial & systems engineering, mechanical engineering & MDO, and robotics.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	1.7

SJR (SCImago Journal Rank)

Year	Value
2024	0.573

Quartile

Year	Value
2024	Q2

h-index

Year	Value
2024	50

Journal Rank

Year	Value
2024	10148

Journal Citation Indicator

Year	Value
2024	714

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science, Engineering and Mathematics, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• A tutorial on geometric programming

  Citation: 836

  Authors: Stephen, Seung-Jean, Lieven, Arash

• Variations and extension of the convex–concave procedure

  Citation: 602

  Authors: Thomas, Stephen

• CVXGEN: a code generator for embedded convex optimization

  Citation: 596

  Authors: Jacob, Stephen

• Review of Nonlinear Mixed-Integer and Disjunctive Programming Techniques

  Citation: 449

  Authors: Ignacio E.

• A review and comparison of solvers for convex MINLP

  Citation: 234

  Authors: Jan, David E., Andreas, Ignacio E.

• A Coupled-Adjoint Sensitivity Analysis Method for High-Fidelity Aero-Structural Design

  Citation: 227

  Authors: Joaquim R.R.A., Juan J., James J.

• On the optimal design of water distribution networks: a practical MINLP approach

  Citation: 183

  Authors: Cristiana, Claudia, Jon, Andrea, Paolo

• Generating Well-Distributed Sets of Pareto Points for Engineering Design Using Physical Programming

  Citation: 169

  Authors: Achille, Christopher A.

• Best practices for comparing optimization algorithms

  Citation: 164

  Authors: Vahid, Warren, Yves

• Pareto Frontier Based Concept Selection Under Uncertainty, with Visualization

  Citation: 158

  Authors: Christopher A., Achille

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