Development and Optimization of Mathematical Models for Operations Research, 2nd Edition

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Engineering Mathematics".

Deadline for manuscript submissions: 31 October 2024 | Viewed by 3121

Special Issue Editors


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Centre for Business and Economics Research, University of Coimbra, Av. Dias da Silva, 3004-512 Coimbra, Portugal
Interests: optimization; applied mathematics; operations research; computer science
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Guest Editor
Department of Production and Systems, School of Engineering, University of Minho, 4704-553 Braga, Portugal
Interests: global optimization; non-linear optimization; integer-mixed programming
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Programming theory of the optimization model, queuing theory of the queuing model, and game theory of the game model are the first three important branches of operations research. The development of mathematical models and their optimization are fundamental for the effective resolution of many problems in operational research. In recent years, increased insights into real-world problems have led to the development of new mathematical models, new optimization algorithms, or both, contributing to the development of a research area with increasing practical relevance.

This Special Issue is dedicated to works at the interface between mathematical modeling, optimization, and operations research, with a special focus on real-world applications. In addition to research papers, high-quality review articles on mathematical models/algorithms developed for a challenging real-world application are welcome.

Topics of interest include (but are not limited to):

  • Mathematical models/Optimization: continuous and discrete optimization, linear and nonlinear optimization, derivative-free optimization, deterministic and stochastic algorithms, nature-inspired algorithms, and other metaheuristic algorithms;
  • Applications: all areas of sciences, engineering, and industry, including economics, medicine, biology, earth sciences, and social sciences.

Dr. Humberto Rocha
Dr. Ana Maria Rocha
Guest Editors

Manuscript Submission Information

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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.

Keywords

  • optimization
  • continuous and discrete optimization
  • linear and nonlinear optimization
  • derivative-free optimization
  • mathematical modeling
  • deterministic and stochastic algorithms
  • operations research
  • mathematical programming
  • programming theory
  • decision theory
  • game theory
  • queuing theory
  • reliability theory
  • real-world applications

Published Papers (2 papers)

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Research

19 pages, 5311 KiB  
Article
Material Property Characterization and Parameter Estimation of Thermoelectric Generator by Using a Master–Slave Strategy Based on Metaheuristics Techniques
by Daniel Sanin-Villa, Oscar Danilo Montoya and Luis Fernando Grisales-Noreña
Mathematics 2023, 11(6), 1326; https://doi.org/10.3390/math11061326 - 09 Mar 2023
Cited by 5 | Viewed by 1186
Abstract
Thermoelectric generators (TEGs) have gained significant interest as a sustainable energy source, due to their ability to convert thermal energy into electrical energy through the Seebeck effect. However, the power output of TEGs is highly dependent on the thermoelectric material properties and operational [...] Read more.
Thermoelectric generators (TEGs) have gained significant interest as a sustainable energy source, due to their ability to convert thermal energy into electrical energy through the Seebeck effect. However, the power output of TEGs is highly dependent on the thermoelectric material properties and operational conditions. Accurate modeling and parameter estimation are essential for optimizing and designing TEGs, as well as for integrating them into smart grids to meet fluctuating energy demands. This work examines the challenges of accurate modeling and parameter estimation of TEGs and explores various optimization metaheuristics techniques to find TEGs parameters in real applications from experimental conditions. The paper stresses the importance of determining the properties of TEGs with precision and using parameter estimation as a technique for determining the optimal values for parameters in a TEG mathematical model that represent the actual behavior of a thermoelectric module. This methodological approach can improve TEG performance and aid in efficient energy supply and demand management, thus reducing the reliance on traditional fossil fuel-based power generation. Full article
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19 pages, 773 KiB  
Article
The Sustainable Home Health Care Process Based on Multi-Criteria Decision-Support
by Filipe Alves, Lino A. Costa, Ana Maria A. C. Rocha, Ana I. Pereira and Paulo Leitão
Mathematics 2023, 11(1), 6; https://doi.org/10.3390/math11010006 - 20 Dec 2022
Cited by 1 | Viewed by 1409
Abstract
The increase in life expectancy has led to a growing demand for Home Health Care (HHC) services. However, some problems can arise in the management of these services, leading to high computational complexity and time-consuming to obtain an exact and/or optimal solution. This [...] Read more.
The increase in life expectancy has led to a growing demand for Home Health Care (HHC) services. However, some problems can arise in the management of these services, leading to high computational complexity and time-consuming to obtain an exact and/or optimal solution. This study intends to contribute to an automatic multi-criteria decision-support system that allows the optimization of several objective functions simultaneously, which are often conflicting, such as costs related to travel (distance and/or time) and available resources (health professionals and vehicles) to visit the patients. In this work, the HHC scheduling and routing problem is formulated as a multi-objective approach, aiming to minimize the travel distance, the travel time and the number of vehicles, taking into account specific constraints, such as the needs of patients, allocation variables, the health professionals and the transport availability. Thus, the multi-objective genetic algorithm, based on the NSGA-II, is applied to a real-world problem of HHC visits from a Health Unit in Bragança (Portugal), to identify and examine the different compromises between the objectives using a Pareto-based approach to operational planning. Moreover, this work provides several efficient end-user solutions, which were standardized and evaluated in terms of the proposed policy and compared with current practice. The outcomes demonstrate the significance of a multi-criteria approach to HHC services. Full article
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