Active special issues

Special issue on MOPTA 2019

Guest Editors: Monica Cojocaru and Tamas Terlaky


Aim and scope

This special issue aims at publishing research work that showcases the interactions between Optimization and Engineering to address important current problems in the specific scientific community. The call to participation encourages submissions from speakers at the Modelling and Optimization: Theory and Applications (MOPTA) 2019, specifically original works showcasing the applications of Optimization to areas such as game theory, health and epidemiology, machine learning/artificial intelligence, quantum information/computing and energy modelling. Beyond this, the issue is open to submissions from any interested authors whose work falls within the areas above. The call is also open to all types of papers, including theoretical, applied, and algorithmic articles, as well as articles that combine these features.

Submission procedure: Submit at https://www.springer.com/mathematics/journal/11081 and select special issue “SI: MOPTA 2019”. 

Deadline: October 31, 2019


Special issue on Technical Operations Research

Guest Editors: Armin Fügenschuh, Ulf Lorenz, Peter F. Pelz

Aim and scope
Technical Operations Research is a bridging discipline that combines elements from engineering (e.g., mechanical, electrical, civil, material), computer science, mathematics and business economics. The aim is to foster quantitative methods in the engineering sciences. A role model is the classic Operations Research which has successfully brought discrete mathematics, combinatorial optimization and other formal disciplines to business engineering and management science. Analogously, Technical Operations Research (TOR) focuses now on technical systems and the control and management of their processes. One example is the combination of individual modules into a larger technical systems in the best possible way, when technical constraints as well as economic considerations have to be taken into account. In this way, TOR is meant to bring OR to new areas of applications, which implies the development of new models and algorithmic methods to solve them to optimality. As a side effect, it stimulates the communication between the different areas of expertise, in particular, between engineers, mathematicians, computer scientists and economists.

Major topics of interests
An ideal submission shows a mixture of the three core TOR disciplines:
  • Problems, models and algorithms: Engineering problems that lead to new TOR research questions, formulated as mathematical optimization problems (e.g., (non-) linear, mixed-integer, ODE/PDE-constrained, robust, stochastic, bilevel, etc.), given rise to the development of new or modified algorithmic approaches for a successful and scalable solution. 
  • Validation and verification: Typically, TOR algorithms use a coarse approximation of physical and technical constraints. Hence their solutions need to be validated and verified by, e.g., simulation models that carry a more refined description of the physics, or by real-world demonstrators and prototypes. This in return shows model-weaknesses and -limits, and can be used to improve formulations and refine models. 
  • Tools for engineers: A major idea of TOR is that the method-oriented disciplines do not replace engineers but extend their capabilities. The goal is to build tools such that the engineers can describe and model a problem at hand, and solve them supported by algorithms. This necessitates the development of tailored modeling languages for describing problem instances as well as interfaces to navigate and explore the solution space in a user-friendly manner.

Important Dates
Papers should be submitted online at https://www.opte-journal.com. Upon manuscript submission, please select the special issue "TOR 2019". Submissions will be peer-reviewed according to the standards of the journal.
  • September 30, 2019: Deadline for submissions of full length papers
  • February 28, 2020: Notification of initial reviews
  • April 30, 2020: Deadline for revisions
  • July 31, 2020: Notification of final reviews
  • September 30, 2020: Submission of final camera-ready manuscripts
  • November 30, 2020: Expected publication

Guest Editors
  •  Armin Fügenschuh, Professor for Engineering Mathematics and Numerics of Optimization, Institute for Mathematics, Brandenburg University of Technology Cottbus-Senftenberg, fuegenschuh@b-tu.de
  • Ulf Lorenz, Professor for Technology Management, School of Economic Disciplines, University of Siegen, ulf.lorenz@uni-siegen.de
  • Peter F. Pelz, Professor for Fluid Systems, Mechanical Engineering, Technische Universität Darmstadt, peter.pelz@fst.tu-darmstadt.de


Special issue on Multiobjective Optimization and Decision Making in Engineering Sciences

Paper submission deadline: 30 November, 2019

Guest Editors

Jussi Hakanen (Faculty of Information Technology, University of Jyväskylä)

Richard Allmendinger (Alliance Manchester Business School, University of Manchester, UK)

Aim and scope

The emergence of advanced technologies and digitalization has been changing our world and leading to a situation where physical assets are being augmented heavily with non-physical assets. In addition to widely used simulation-based optimization, data-driven optimization approaches have become more popular in engineering sciences due to availability of large amounts of data collected in every field (e.g. from IoT, sensors, experimental measurements etc.). Therefore, the effective combination of data and advanced engineering and management technologies and skills is becoming a key asset to a company urging the need to rethink how to tackle modern decision making problems. The consideration of various competing factors related to business, technical, workforce, safety and environmental aspects further increases the complexity of decision making and leads to multiple criteria decision making (MCDM) problems. This special issue focuses on the intersection between Engineering, Data Science, Multiple Criteria Decision Making (MCDM) and Multiobjective Optimization (MO). The development of new models and algorithmic methods to solve such problems is in the focus as much as the application of these concepts to real problems.

The aim of the issue is to bring together academics and practitioners with different expertise, in particular, in engineering, computer science, mathematics, data science and business. 

This special issue is connected to but not restricted to papers presented at the 25th International Conference on Multiple Criteria Decision Making, MCDM2019 (to be held in Istanbul, Turkey, in June 2019).

Major topics of interest

All submissions related to the development/application of multi/many-objective optimization in engineering are welcome. Especially, submissions considering novel approaches combining engineering and data science are highly encouraged. Topics of interest (but not limited to) include:

  • Preference-based approaches actively incorporating human decision makers
  • Data-driven methods and their combination with simulation-based approaches
  • Applications in engineering sciences where multi/many-objective optimization has been used to make more informed decisions (e.g. advanced manufacturing, material sciences and digital technology)
  • MCDM system development aimed at practical use in engineering enabling interactive participation of the decision maker (visualization, decision support, graphical user interfaces, automatic configuration and tuning of optimization and decision making algorithms)
  • Hybrid methodologies combining mathematical programming, evolutionary computation and/or machine learning
  • Approaches for computationally expensive (black-box) multi/many-objective problems and/or challenges in MCDM
  • Methods to deal with problem challenges arising in engineering sciences such as uncertainty, dynamic landscapes/constraints, noisy functions/data, robustness requirements etc.
  • Test/benchmark problems/simulators and performance measures to validate optimization and decision making approaches in engineering sciences, large-scale/mixed type/highly constrained problems

Submission instructions

Papers should be submitted online at https://www.opte-journal.com and the submission deadline for full-length papers is November 30, 2019. Upon manuscript submission, please select the special issue "MCDM 2019". Submissions will be peer-reviewed according to the standards of the journal. Manuscripts will be processed as they arrive and will be published online as soon as they are accepted. For planning purposes, interested authors are encouraged to email a tentative title to the guest editors.

Contact

Please feel free to contact us in case you have any questions

Jussi Hakanen: jussi.hakanen@jyu.fi <mailto:jussi.hakanen@jyu.fi>

Richard Allmendinger: richard.allmendinger@manchester.ac.uk <mailto:richard.allmendinger@manchester.ac.uk>


Special issue on PDE-Constrained Optimization

Guest Editors:
Michael Ulbrich, Professor, Chair of Mathematical Optimization, Department of Mathematics, Technical University of Munich mulbrich@ma.tum.de.
Boris Vexler, Professor, Chair of Optimal Control, Department of Mathematics, Technical University of Munich vexler@ma.tum.de.

Aim:
This call aims at publishing research work on PDE-constrained optimization connected to applications in engineering. The call is open to all types of papers, including theoretical, applied, and algorithmic articles, or combinations of them.

Theme:
The accurate modeling of complex physical and technical systems heavily relies on PDEs. The resulting systems live in infinite-dimensional function spaces and can involve nonlinearity, nonsmoothness, or uncertainty. Optimization with PDE constraints is the enabling discipline for analyzing and solving highly important problem classes connected to these systems, such as: shape and topology optimization, optimal control, inverse problems, parameter identification, etc. Beyond more traditional applications, the field is increasingly interacting with other timely and important areas, such as uncertainty quantification, data science, or mathematical imaging. Studying the theoretical and numerical aspects of PDE-constrained optimization problems in their original function space setting and tying the developments closely to the latest theoretical and computational advances for PDEs are key elements for a strong theory and for robust, mesh-independent solvers. Mathematically, PDE-constrained optimization is as rich as its numerous applications: It combines theoretical and practical methodology from optimization, PDEs, functional analysis, nonsmooth and variational analysis, numerical analysis, and scientific computing; it also can involve probability and measure theory.

This special issues targets at showcasing the latest advances in PDE-constrained optimization at the intersection of mathematics and engineering applications.

Submission Procedure:
Please submit to the Optimization and Engineering (OPTE) journal at https://www.springer.com/mathematics/journal/11081 and select special issue “SI: PDE 2019”. All sub- missions must be original and may not be under review by another publication. Interested authors should consult the journal’s “Instructions for Authors”, at http://www.springer.com/ mathematics/journal/11081. All submitted papers will be reviewed on a peer review basis as soon as they are received. Accepted papers will be available at Online First until the complete Special Issue appears.

All inquiries should be directed to the attention of:

Michael Ulbrich, Subject Editor and Guest Editor (mulbrich@ma.tum.de)
Boris Vexler, Guest Editor (vexler@ma.tum.de)
Optimization and Engineering (OPTE) journal