Advances in Mathematical Modeling, Analysis and Optimization

A special issue of Axioms (ISSN 2075-1680). This special issue belongs to the section "Mathematical Analysis".

Deadline for manuscript submissions: 31 May 2024 | Viewed by 1214

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Institute of Information Technology, Lodz University of Technology, 90-924 Lodz, Poland
Interests: mathematical modeling; optimization of complex systems; combinatorial optimization; packing and covering problems; computational intelligence
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Mathematical Modelling and Artificial Intelligence Department, National Aerospace University “Kharkiv Aviation Institute”, 61070 Kharkiv, Ukraine
Interests: agent-based simulation; artificial intelligence; multiagent simulation; machine learning; infectious diseases simulation; data-driven medicine
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue highlights the latest advances and trends in the interrelated fields of mathematical modeling, analysis, and optimization. Particular attention is expected to be paid to the development and implementation of innovative mathematical models, advanced analytical methods and optimization strategies that can potentially solve complex real-world problems in a wide range of disciplines, including engineering, data science, operations research, economics, and biological and physical sciences. The scope of this Special Issue is broad and includes theoretical studies, practical applications, and case studies involving the innovative use of mathematical modeling, analysis, and optimization techniques.

Articles that discuss various approaches to optimizing complex systems are also welcome, including multi-objective, global, combinatorial, stochastic optimization, and other advanced strategies. This Special Issue is intended to serve as a platform for researchers, scientists, and industry professionals to share new discoveries, promote intellectual discourse and cross-fertilization of ideas, and inspire further advances in these exciting fields. This Special Issue will complement the existing scientific literature by providing a comprehensive and up-to-date overview of modern mathematical modeling, analysis, and optimization. It will show how these fields are evolving in response to new challenges and opportunities, especially in the context of big data, artificial intelligence, and complex systems analysis. In addition, by combining theoretical and applied research, this issue will bridge the gap between abstract mathematical concepts and practical problem solving, thereby enriching the overall body of knowledge in these interrelated areas.

Prof. Dr. Yakovlev Sergiy
Dr. Dmytro Chumachenko
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. Axioms is an international peer-reviewed open access monthly 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 2400 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

  • mathematical modeling
  • complex system
  • system analysis
  • optimization
  • operations research
  • computational intelligence
  • machine learning
  • data science

Published Papers (1 paper)

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Research

22 pages, 6252 KiB  
Article
Research on the Modeling of Automatic Pricing and Replenishment Strategies for Perishable Goods with Time-Varying Deterioration Rates
by Aihua Gu, Zhongzhen Yan, Xixi Zhang and Yongsheng Xiang
Axioms 2024, 13(1), 62; https://doi.org/10.3390/axioms13010062 - 19 Jan 2024
Cited by 1 | Viewed by 896
Abstract
This paper focuses on the modeling of automatic pricing and replenishment strategies for perishable products with time-varying deterioration rates based on an improved SVR-LSTM-ARIMA hybrid model. This research aims to support supermarkets in planning future strategies, optimizing category structure, reducing loss rates, and [...] Read more.
This paper focuses on the modeling of automatic pricing and replenishment strategies for perishable products with time-varying deterioration rates based on an improved SVR-LSTM-ARIMA hybrid model. This research aims to support supermarkets in planning future strategies, optimizing category structure, reducing loss rates, and improving profit margins and service quality. Specifically, the paper selects perishable vegetables as the research category and calculates the cost-plus ratio for each vegetable category. Correlation analysis is conducted with total sales, and a non-parametric relationship curve is obtained using support vector regression for nonlinear fitting. The long and short memory recurrent neural network is then used to predict sales volume, and a pricing strategy is calculated based on the fitting curve. Additionally, the paper establishes a correlation between loss rate and shelf life, corrects the daily average sales volume index, and solves the problem of quantity and category of replenishment using a backpack problem approach. By considering multiple constraints, a quantitative category replenishment volume and pricing strategy is obtained. The mathematical model proposed in this paper addresses the replenishment and pricing challenges faced by supermarkets, aiming to improve revenue and reduce loss while meeting market requirements. Full article
(This article belongs to the Special Issue Advances in Mathematical Modeling, Analysis and Optimization)
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