New Insights into Optimal Control and Applications in Automotive Engineering

A special issue of Mathematics (ISSN 2227-7390).

Deadline for manuscript submissions: 31 January 2025 | Viewed by 979

Special Issue Editor


E-Mail Website
Guest Editor
Faculty of Industrial Engineering and Robotics, University Politehnica of Bucharest, 060042 Bucharest, Romania
Interests: optimal control models; optimization problems; automotive systems; automotive design

Special Issue Information

Dear Colleagues,

Connected with algorithms, computer science, artificial intelligence, machine learning, and experimental and theoretical approaches of applied mathematics are visibly present in various fields of industry and services to expand knowledge boundaries and improve global performance.

Modelling, optimisation, and estimation in order to better control the variation of processes and better foresee the potential results are of significant interest to businesses, with a tangible impact and promising potential revenue. Meanwhile, optimal control theory is essential for engineering in terms of product design, processes operation and management, but also for business models and new services in terms of planning, organisation, resources management, finance, marketing and sales, revealing numerous applications in industry.

This Special Issue aims to build a network for engineers, mathematicians, researchers, and academics to share applied mathematics contributions. This Special Issue concentrates on the automotive industry as one of the most dynamic fields worldwide that is experiencing significant changes due to artificial intelligence technologies, but submissions do not need to be restricted to this field.

The topics of particular interest for this Special Issue include but are not limited to experimental and theoretical developments, such as:

  • Examples of controlled dynamics;
  • Optimal control models;
  • Multi-objective constraint optimization problems;
  • Multidisciplinary optimization problems;
  • Practical approaches and methods for design and process control in automotive systems;
  • Optimization in performance improvement;
  • Links between design and industrial processes;
  • Business models and performance control.

Prof. Dr. Irina Severin
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

17 pages, 1839 KiB  
Article
Approaches for Streamlining Performance Control by Monte Carlo Modeling
by Elena Corina Cipu, Ruxandra Ioana Cipu and Ştefania Maria Michnea
Mathematics 2024, 12(7), 1090; https://doi.org/10.3390/math12071090 - 4 Apr 2024
Viewed by 622
Abstract
For decades, cancer has remained a persistent health challenge; this project represents a significant stride towards refining treatment approaches and prognostic insights. Proton beam therapy, a radiation therapy modality employing high-energy protons to target various malignancies while minimizing damage to adjacent healthy tissue, [...] Read more.
For decades, cancer has remained a persistent health challenge; this project represents a significant stride towards refining treatment approaches and prognostic insights. Proton beam therapy, a radiation therapy modality employing high-energy protons to target various malignancies while minimizing damage to adjacent healthy tissue, holds immense promise. This study analyzes the relationship between delivered radiation doses and patient outcomes, using various approximation functions and graphical representations for comparison. Statistical analysis is performed through the Monte Carlo method based on repeated sampling to estimate the variables of interest in this analysis, namely, the survival rates, financial implications, and medical effectiveness of proton beam therapy. To this end, open-source data from research centers that publish patient outcomes were utilized. The second study considered the estimation of pay gaps that can have long-lasting effects, leading to differences in retirement savings, wealth accumulation, and overall financial security. After finding a representative sample containing the relevant variables that contribute to pay gaps, such as gender, race, experience, education, and job role, MC modeling is used to simulate a range of possible pay gap estimates. Based on the Monte Carlo results, a sensitivity analysis is performed to identify which variables have the most significant impact on pay gaps. Full article
Show Figures

Figure 1

Back to TopTop