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REDUCE – A Python Module for Reducing Inconsistency in Pairwise Comparison Matrices

Kuraś Paweł, Strzałka Dominik, Kowal Bartosz, Mazurek Jiří

Advances in Science and Technology. Research Journal

2023

Vol. 17, no 4

227--234

This paper introduces REDUCE, a Python module designed to minimize inconsistency in multiplicative pairwise comparisons (PC), a fundamental technique in Multi-Criteria Decision Making (MCDM). Pairwise comparisons are extensively used in various fields, including engineering science and numerical simulation methods, to compare different options based on a set of criteria. However, human errors in perception and judgment often lead to inconsistencies in pairwise comparison matrices (PCM). REDUCE addresses this issue by implementing several algorithms that identify and correct inaccurate data in PCMs, thereby reducing the inconsistency ratio. These algorithms do not require expert intervention, making REDUCE a valuable tool for both scientific research and small to medium enterprises that may not have access to costly commercial software or dedicated decision-making experts. The main functionality of the module is incorporating iterative algorithms for inconsistency reduction. The REDUCE library, written in Python and utilizing auxiliary libraries such as NumPy, SciPy, and SymPy, offers 21 functions categorized into data input helpers, consistency ratio (CR) reduction algorithms, PCM indexes, and support functions. Performance testing indicates that the library can efficiently handle matrices of varying sizes, particularly those ranging from 3x3 to 10x10, and its use significantly accelerates the process compared to spreadsheets, especially when dealing with large quantities of matrices. The library has already been used in several research papers and application tools, and its availability as a free resource opens up opportunities for small and medium-sized enterprises to leverage multi-criteria decision-making methods. Currently, there are no publicly available libraries for this solution. The authors believe that the proposed module may contribute to do better decision-making process in pairwise comparisons, not only for the circle of scientists but also for small and medium enterprises that usually cannot afford expensive commercial software and do not employ full-time experts in decision-making as they rely on the experience of their employees and free online resources. It should also contributes to the transition to Industry 4.0 and advances research in fields such as fuzzy logic, preference programming, and constructive consistent approximations.

Software outlines for decisions making support in oil and gas engineering

Chesanovskyy Mykola, Kravtsiv Kostiantyn, Protsiuk Volodymyr, Poteriailo Liudmyla

Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska

2021

z. 151

81--99

Purpose: The aim of this study is to develop an architecture of enterprise solutions that allow real-time (or simulated) extraction, storage and analysis of parameterized data from high- resolution sensors to more accurately predict the potential course of technological processes in the industry and solving of related logistics tasks. Design/methodology/approach: The development of an integration architecture based on appropriate Web tools for viewing and collaborating on corporate information of the oil and gas industry will allow full operational decision-making on this basis, guided by the values of relevant controlled parameters and imposed on them and the process as a whole relevant constraints in general are the methodological grounds of the research from the theoretical and subject domain scope. The functionality of the artificial intelligence system should be reduced to sending signals to the controller in order to modify the controlled parameters through the appropriate instructions. At the theoretical level, measurement, interpretation and control will take place either on the surface, or on the bore, or in both places at the same time. Findings: There were explored software outlines for making possible the creation of the desired findings for new and better business processes and technological innovations in the domestic gas and oil industries based on intelligent information solutions. As proposed in this study, optimal flexibility and forward performance will only be achieved through the use of the cloud as a platform for tomorrow's technological challenges in the oil and gas industry. Originality/value: The newly developed focus on novel class of increasing domestic business efficiency will generally encourage oil and gas companies to develop their information architecture in the direction of knowledge-based systems and solutions, especially when controlling the drilling of oil and gas wells in terms of incomplete, inaccurate and poorly structured information from sensors.

The application of Business Intelligence systems in logistics. review of selected practical examples

Grabińska Aleksandra, Ziora Leszek

System Safety : Human - Technical Facility - Environment

2019

Vol. 1, nr 1

1028--1035

The goal of the paper is to present the application of Business Intelligence systems belonging to the area of business analytics in the domain of logistics and particularly indicate its role and meaning in supporting logistics decision making processes. Its content embraces the characteristic of BI systems, its functionality, construction and benefits resulting from its implementation. The paper also presents review of research and case studies connected to the BI usage in such areas of logistics as optimization of supply chain, managerial dashboard design and improvement of business processes.