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Mathematics
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Mathematical Methods and Models in Software Engineering
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Mathematical Methods and Models in Software Engineering

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

Deadline for manuscript submissions: closed (20 May 2023) | Viewed by 12430

Special Issue Editors

Prof. Dr. Todor Stoilov

E-Mail Website
Guest Editor
Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, BG-1113 Sofia, Bulgaria
Interests: optimization; multilevel systems; control systems
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Krasimira Stoilova

E-Mail Website
Guest Editor
Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, BG-1113 Sofia, Bulgaria
Interests: bi-level optimization; hierarchical systems; real time control
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The mathematical methods and modelling targets formal presentation and quantification of problems, which solutions have wide applications in practice for activities as control, planning, decision making, management of complex systems. Particularly, the main tools for solving the every day problems are in information, computer and communication environments. These computational and information environments are running under software tools, which operate under formal methods and models. This special issue targets illustration of different solutions, which take part in such virtual environments. Potential topics, which are considered to be presented in this special issue, are listed as: advances in information systems and technologies, digital transformation of processes, advances in software and system engineering, Information system management, Internet of things, challenges and applications, autonomic computing, computer aspects of numerical algorithms, scalable computing, advances in network systems and applications, software engineering, knowledge acquisition and management. We expect the submitted papers to present solutions and examples based on mathematical optimization, algorithms for application domains, approximation algorithms, operation research approaches and others formal approaches. We are inviting submissions to the Mathematics Special issue on “Mathematical Methods and Models in Software Engineering”.

Prof. Dr. Todor Stoilov
Prof. Dr. Krasimira Stoilova
Guest Editors

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.

Keywords

  • optimization
  • algorithms for application domains
  • software engineering
  • network and information systems

Published Papers (5 papers)

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Research

31 pages, 2037 KiB  
Article
Effort and Cost Estimation Using Decision Tree Techniques and Story Points in Agile Software Development
by Eduardo Rodríguez Sánchez, Eduardo Filemón Vázquez Santacruz and Humberto Cervantes Maceda
Mathematics 2023, 11(6), 1477; https://doi.org/10.3390/math11061477 - 17 Mar 2023
Cited by 9 | Viewed by 5540
Abstract
Early effort estimation is important for efficiently planning the use of resources in an Information Technology (IT) project. However, limited research has been conducted on the topic of effort estimation in agile software development using artificial intelligence. This research project contributes to strengthening [...] Read more.
Early effort estimation is important for efficiently planning the use of resources in an Information Technology (IT) project. However, limited research has been conducted on the topic of effort estimation in agile software development using artificial intelligence. This research project contributes to strengthening the use of hybrid models composed of algorithmic models and learning oriented techniques as a project-level effort estimation method in agile frameworks. Effort estimation in agile methods such as Scrum uses a story point approach that measures, using an arithmetic scale, the effort required to complete a release of the system. This project relied on labeled historical data to estimate the completion time measured in days and the total cost of a project set in Pakistani rupees (PKR). using a decision tree, random forest and AdaBoost to improve the accuracy of predictions. Models were trained using 10-fold cross-validation and the relative error was used as a comparison with literature results. The bootstrap aggregation (bagging) ensemble made of the three techniques provides the highest accuracy, and project classification also improves the estimates. Full article
(This article belongs to the Special Issue Mathematical Methods and Models in Software Engineering)
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22 pages, 2142 KiB  
Article
An Efficient Hybrid of an Ant Lion Optimizer and Genetic Algorithm for a Model Parameter Identification Problem
by Olympia Roeva, Dafina Zoteva, Gergana Roeva and Velislava Lyubenova
Mathematics 2023, 11(6), 1292; https://doi.org/10.3390/math11061292 - 7 Mar 2023
Cited by 3 | Viewed by 1579
Abstract
The immense application of mathematical modeling for the improvement of bioprocesses determines model development as a topical field. Metaheuristic techniques, especially hybrid algorithms, have become a preferred tool in model parameter identification. In this study, two efficient algorithms, the ant lion optimizer (ALO), [...] Read more.
The immense application of mathematical modeling for the improvement of bioprocesses determines model development as a topical field. Metaheuristic techniques, especially hybrid algorithms, have become a preferred tool in model parameter identification. In this study, two efficient algorithms, the ant lion optimizer (ALO), inspired by the interaction between antlions and ants in a trap, and the genetic algorithm (GA), influenced by evolution and the process of natural selection, have been hybridized for the first time. The novel ALO-GA hybrid aims to balance exploration and exploitation and significantly improve its global optimization ability. Firstly, to verify the effectiveness and superiority of the proposed work, the ALO-GA is compared with several state-of-the-art hybrid algorithms on a set of classical benchmark functions. Further, the efficiency of the ALO-GA is proved in the parameter identification of a model of an Escherichia coli MC4110 fed-batch cultivation process. The obtained results have been studied in contrast to the results of various metaheuristics employed for the same problem. Hybrids between the GA, the artificial bee colony (ABC) algorithm, the ant colony optimization (ACO) algorithm, and the firefly algorithm (FA) are considered. A series of statistical tests, parametric and nonparametric, are performed. Both numerical and statistical results clearly show that ALO-GA outperforms the other competing algorithms. The ALO-GA hybrid algorithm proposed here has achieved an improvement of 6.5% compared to the GA-ACO model, 7% compared to the ACO-FA model, and 7.8% compared to the ABC-GA model. Full article
(This article belongs to the Special Issue Mathematical Methods and Models in Software Engineering)
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25 pages, 3982 KiB  
Article
Studying the Effect of Introducing Chaotic Search on Improving the Performance of the Sine Cosine Algorithm to Solve Optimization Problems and Nonlinear System of Equations
by Mohammed A. El-Shorbagy and Fatma M. Al-Drees
Mathematics 2023, 11(5), 1231; https://doi.org/10.3390/math11051231 - 2 Mar 2023
Cited by 2 | Viewed by 1298
Abstract
The development of many engineering and scientific models depends on the solution of nonlinear systems of equations (NSEs), and the progress of these fields depends on their efficient resolution. Due to the disadvantages in solving them with classical methods, NSEs are amenable to [...] Read more.
The development of many engineering and scientific models depends on the solution of nonlinear systems of equations (NSEs), and the progress of these fields depends on their efficient resolution. Due to the disadvantages in solving them with classical methods, NSEs are amenable to modeling as an optimization issue. The purpose of this work is to propose the chaotic search sine cosine algorithm (CSSCA), a new optimization approach for solving NSEs. CSSCA will be set up so that it employs a chaotic search to get over the limitations of optimization techniques like a lack of diversity in solutions, exploitation’s unfair advantage over exploration, and the gradual convergence of the optimal solution. A chaotic logistic map has been employed by many studies and has demonstrated its effectiveness in raising the quality of solutions and offering the greatest performance. So, it is used as a local search strategy. Three kinds of test functions—unimodal, multimodal, and composite test functions—as well as numerous NSEs—combustion problems, neurophysiology problems, arithmetic application, and nonlinear algebraic equations—were employed to assess CSSCA. To demonstrate the significance of the changes made in CSSCA, the results of the recommended algorithm are contrasted with those of the original SCA, where CSSCA’s average improvement rate was roughly 12.71, demonstrating that it is very successful at resolving NSEs. Finally, outcomes demonstrated that adding a chaotic search to the SCA improves results by modifying the chaotic search’s parameters, enabling better outcomes to be attained. Full article
(This article belongs to the Special Issue Mathematical Methods and Models in Software Engineering)
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11 pages, 2787 KiB  
Article
Design of Fuzzy and Conventional Controllers for Modeling and Simulation of Urban Traffic Light System with Feedback Control
by Boriana Vatchova and Yordanka Boneva
Mathematics 2023, 11(2), 373; https://doi.org/10.3390/math11020373 - 10 Jan 2023
Cited by 3 | Viewed by 1302
Abstract
Traffic patterns in urban areas present a complex and dynamic system that is characterized by inherent uncertainties. The presented study is a traffic light control system with feedback. The controller of the system is designed in a fuzzy and conventional way and is [...] Read more.
Traffic patterns in urban areas present a complex and dynamic system that is characterized by inherent uncertainties. The presented study is a traffic light control system with feedback. The controller of the system is designed in a fuzzy and conventional way and is applied to a network of two junctions. The verification is performed using the MATLAB fuzzy toolbox platform (for designing the fuzzy controller) and Aimsun platform for microsimulation of the two junctions using the two types of controllers. To accomplish the control of the system a fuzzy controller on heuristic rules proposed to allow adaptive traffic control on signalized junctions in urban environments. The Fuzzy Toolbox in MATLAB is used to simulate the fuzzy controller. The Aimsun traffic simulator is used to model and simulate a traffic network of two intersections. The green light duration in the Aimsun model is based on the results for the two controllers from two separated experiments. Simulations of Aimsun models with the two types of controllers, the fuzzy and the conventional one, are compared. The experiment is performed under the premise that the traffic flow is oversaturated. Findings show that in a network of two junctions both controllers perform in a similar manner for the first junction. However, for the second junction, the fuzzy controller tends to have some advantages over the conventional controller with regard to higher traffic flow. In conclusion, the overall performance of the fuzzy controller is better than the one of the conventional controller, but further research is needed for more complex traffic networks. Full article
(This article belongs to the Special Issue Mathematical Methods and Models in Software Engineering)
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19 pages, 2991 KiB  
Article
An Algorithm for Business Management Based on Portfolio Optimization
by Todor Stoilov and Krasimira Stoilova
Mathematics 2022, 10(22), 4262; https://doi.org/10.3390/math10224262 - 14 Nov 2022
Viewed by 1358
Abstract
An algorithm is derived for active business management. The key component of the algorithm is the definition and solution of an appropriate portfolio problem. For the last one, the disbursements for the business management are regarded as potential portfolio resources. For the portfolio [...] Read more.
An algorithm is derived for active business management. The key component of the algorithm is the definition and solution of an appropriate portfolio problem. For the last one, the disbursements for the business management are regarded as potential portfolio resources. For the portfolio definition, the increases or decreases of the disbursements are assumed to be the assets, whose weights are found as solutions from the portfolio optimization problem. These solutions recommend the reallocation of the resources between different disbursements, which increases the income of the business entity. The definition and solution of this portfolio problem are made sequentially in time, and the obtained solutions are applied as recommendations for future business management steps. An algorithm for business management, based on the sliding mode of repetitive definitions and solutions of portfolio problems with historical data of last disbursements, gives recommendations for the reallocation of resources for the next future period of management. The algorithm is numerically tested with real data on animal husbandry from Bulgaria. The empirical results demonstrate an advantage in increasing the husbandry income in comparison with the lack of such an active business policy. The algorithm can be implemented as a software solution in an appropriate programming system, supporting fintech service for active business management. Full article
(This article belongs to the Special Issue Mathematical Methods and Models in Software Engineering)
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