Information for Business and Management–Software Development for Data Processing and Management, 2nd Edition

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Applications".

Deadline for manuscript submissions: 31 December 2024 | Viewed by 1231

Special Issue Editor


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Guest Editor
Institute of Information Technology, Lodz University of Technology, 90-924 Lodz, Poland
Interests: software engineering; information systems security; multi-agent-based systems; cloud computing; internet of things; mobile security; blockchain; data analysis; machine learning; data processing; distributed systems
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Special Issue Information

Dear Colleagues,

Today, data and information are among the most important resources in various aspects of our life and economy. Data and information are created, generated, collected, stored, and then processed and shared in various ways. All these activities are performed with the participation of contemporary software, applications, IT systems and their components.

Thus, in addition to creating the software itself, it is becoming increasingly crucial to manage the data and information that the software uses, processes and stores. Hence, not only are the software itself and the process of its development vital, but also information management at the appropriate level and the maintenance of a sufficiently high level of data protection, information and its flow.

The process of software development and information management are becoming increasingly interconnected and dependent, striving to develop and support a modern society based on knowledge and modern technologies.

Therefore, this Special Issue aims to exhibit various aspects of software creation and development, which are designed for the rapid, easy and secure processing and management of data and information.

The areas of interest for this Special Issue include the following topics: software analysis and design for the processing and management of data and information, software deployment for data processing, business analysis, business rules, requirements engineering, software development process, information management system, knowledge management solutions, software for security and privacy of data, software for data mining, and software for knowledge management.

Prof. Dr. Aneta Poniszewska-Maranda
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. Information 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 1600 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

  • software engineering for data
  • requirements engineering for information management
  • data processing and management
  • business analysis
  • knowledge management
  • security and privacy of data
  • software for data mining

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Published Papers (1 paper)

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Research

15 pages, 1033 KiB  
Article
Two Lot-Sizing Algorithms for Minimizing Inventory Cost and Their Software Implementation
by Marios Arampatzis, Maria Pempetzoglou and Athanasios Tsadiras
Information 2024, 15(3), 167; https://doi.org/10.3390/info15030167 - 15 Mar 2024
Viewed by 1042
Abstract
Effective inventory management is crucial for businesses to balance minimizing holding costs while optimizing ordering strategies. Monthly or sporadic orders over time may lead to high ordering or holding costs, respectively. In this study, we introduce two novel algorithms designed to optimize ordering [...] Read more.
Effective inventory management is crucial for businesses to balance minimizing holding costs while optimizing ordering strategies. Monthly or sporadic orders over time may lead to high ordering or holding costs, respectively. In this study, we introduce two novel algorithms designed to optimize ordering replenishment quantities, minimizing total replenishment, and holding costs over a planning horizon for both partially loaded and fully loaded trucks. The novelty of the first algorithm is that it extends the classical Wagner–Whitin approach by incorporating various additional cost elements, stock retention considerations, and warehouse capacity constraints, making it more suitable for real-world problems. The second algorithm presented in this study is a variation of the first algorithm, with its contribution being that it incorporates the requirement of several suppliers to receive order quantities that regard only fully loaded trucks. These two algorithms are implemented in Python, creating the software tool called “Inventory Cost Minimizing tool” (ICM). This tool takes relevant data inputs and outputs optimal order timing and quantities, minimizing total costs. This research offers practical and novel solutions for businesses seeking to streamline their inventory management processes and reduce overall expenses. Full article
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