World's Best Scientists 2026 revealed!
Optimization and Engineering
H-index 21

Optimization and Engineering

1389-4420

Published by: Springer

https://www.springer.com/journal/11081

Ranking & Metrics

Discipline name Position Best Scientists Publications D-Index
Computer Science 536 25 34 11
Engineering and Technology 602 43 73 14

Additional Metrics

Number of Best Scientists*: 115
Documents by Best Scientists*: 158
Top 100 Ranked Scientists*: 5
SCIMAGO H-index: 50
SCIMAGO SJR: 0.573
Impact Factor: 1.7

Overview

Top Research Topics at Optimization and Engineering?

Optimization and Engineering primarily tackles Mathematical optimization, Financial engineering, Optimization problem, Algorithm and Applied mathematics. The studies on Mathematical optimization discussed can also contribute to research in the domains of Set (abstract data type) and Nonlinear programming, Nonlinear system. While work presented in the journal provided substantial information on Financial engineering, it also covered topics in Linear programming, Scheduling (production processes), Engineering design process and Operations research.

It connects research in Optimization problem with the related topic of Optimal design.

  • Mathematical optimization (56.78%)
  • Financial engineering (27.84%)
  • Optimization problem (18.93%)

What are the most cited papers published in the journal?

  • A tutorial on geometric programming (939 citations)
  • CVXGEN: a code generator for embedded convex optimization (585 citations)
  • Review of Nonlinear Mixed-Integer and Disjunctive Programming Techniques (509 citations)

Research areas of the most cited articles at Optimization and Engineering:

The published papers explore disciplines such as Mathematical optimization, Financial engineering, Optimization problem, Global optimization and Nonlinear programming. Algorithm and Engineering design process are some topics wherein Mathematical optimization research discussed in the journal publications has an impact. The most cited publications focus on Optimization problem but sometimes tackle the closely related topic of Optimal design which is concerned with Control theory.

What topics the last edition of the journal is best known for?

  • Statistics
  • Mathematical optimization
  • Artificial intelligence

The previous edition focused in particular on these issues:

The primary areas of discussion in Optimization and Engineering are Mathematical optimization, Financial engineering, Optimization problem, Applied mathematics and Algorithm. The Mathematical optimization works featured in Optimization and Engineering incorporate elements from Nonlinear programming and Set (abstract data type). The work on Financial engineering tackled in it brings together disciplines like Context (language use), Robust optimization, Industrial engineering, Key (cryptography) and Operations research.

The journal focuses on Optimization problem but the discussions also offer insight into other areas such as Bayesian optimization, Global optimization, Decomposition (computer science), Function (mathematics) and Computation. Inverse, Inverse problem and Hilbert space are some topics wherein Applied mathematics research discussed in it have an impact. Some problems in Algorithm that were presented in it overlapped with concepts under Convergence (routing) and Robustness (computer science).

The most cited articles from the last journal are:

  • Optimization study on extraction of antioxidants from plum seeds ( Prunus domestica L.) (9 citations)
  • Nonlinear optimization of district heating networks (8 citations)
  • A comparison of particle swarm optimization and genetic algorithm for daily rainfall-runoff modelling: a case study for Southeast Queensland, Australia (8 citations)

Papers citation over time

A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

The top authors publishing in Optimization and Engineering (based on the number of publications) are:

  • Ignacio E. Grossmann (16 papers) published 5 papers at the last edition, 4 more than at the previous edition,
  • Stephen Boyd (14 papers) published 4 papers at the last edition, 3 more than at the previous edition,
  • Yoshihiro Kanno (10 papers) published 1 paper at the last edition the same number as at the previous edition,
  • Nikolaos V. Sahinidis (8 papers) published 2 papers at the last edition, 1 more than at the previous edition,
  • Tamás Terlaky (7 papers) published 3 papers at the last edition.

The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.

Only papers with recognized affiliations are considered

The top affiliations publishing in Optimization and Engineering (based on the number of publications) are:

  • Carnegie Mellon University (28 papers) published 6 papers at the last edition, 3 more than at the previous edition,
  • Stanford University (21 papers) published 6 papers at the last edition, 4 more than at the previous edition,
  • École Polytechnique de Montréal (16 papers) published 1 paper at the last edition, 1 less than at the previous edition,
  • RWTH Aachen University (13 papers) published 2 papers at the last edition, 1 less than at the previous edition,
  • University of Waterloo (12 papers) published 2 papers at the last edition, 1 less than at the previous edition.

The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

During the most recent 2021 edition, 2.58% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 19.87% were posted by at least one author from the top 10 institutions publishing in the journal. Another 9.27% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 10.60% of all publications and 60.26% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

  • Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
  • Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
  • Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
  • Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
  • Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

Top Publications

  • Bayesian optimization using deep Gaussian processes with applications to aerospace system design

    Ali Hebbal;Ali Hebbal;Loïc Brevault;Mathieu Balesdent;El-Ghazali Talbi

    (2021)
    63 Citations
  • Identifying material parameters in crystal plasticity by Bayesian optimization

    Jannick Kuhn;Jonathan Spitz;Petra Sonnweber-Ribic;Matti Schneider

    (2021)
    56 Citations
  • Electric power infrastructure planning under uncertainty: stochastic dual dynamic integer programming (SDDiP) and parallelization scheme

    Cristiana L. Lara;John D. Siirola;Ignacio E. Grossmann

    (2020)
    41 Citations
  • Obey validity limits of data-driven models through topological data analysis and one-class classification

    Artur M. Schweidtmann;Artur M. Schweidtmann;Jana M. Weber;Christian Wende;Linus Netze

    (2021)
    39 Citations
  • Joint stochastic short-term production scheduling and fleet management optimization for mining complexes

    Christian Both;Roussos Dimitrakopoulos

    (2020)
    38 Citations
  • An efficient 146-line 3D sensitivity analysis code of stress-based topology optimization written in MATLAB

    Hao Deng;Praveen S. Vulimiri;Albert C. To

    (2021)
    36 Citations
  • Pyomo.GDP: an ecosystem for logic based modeling and optimization development

    Qi Chen;Emma S. Johnson;David E. Bernal;Romeo Valentin

    (2021)
    35 Citations
  • Alternating Maximization: Unifying Framework for 8 Sparse PCA Formulations and Efficient Parallel Codes

    Peter Richtárik;Martin Takáč;Selin Damla Ahipaşaoğlu

    (2021)
    30 Citations
  • Working fluid selection for organic rankine cycles via deterministic global optimization of design and operation

    Wolfgang R. Huster;Artur M. Schweidtmann;Alexander Mitsos

    (2020)
    27 Citations
  • Robust optimization in power systems: a tutorial overview

    Antonio J. Conejo;Xuan Wu

    (2021)
    26 Citations

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