Vishwas Deep Joshi¹, Priya Agarwal¹, Lenka Čepová², Huda Alsaud³, Ajay Kumar^4,*, B. Swarna⁵, Ashish Kumar⁶

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.1, pp. 969-1011, 2025, DOI:10.32604/cmes.2025.063996 - 31 July 2025

Abstract In a world where supply chains are increasingly complex and unpredictable, finding the optimal way to move goods through transshipment networks is more important and challenging than ever. In addition to addressing the complexity of transportation costs and demand, this study presents a novel method that offers flexible routing alternatives to manage these complexities. When real-world variables such as fluctuating costs, variable capacity, and unpredictable demand are considered, traditional transshipment models often prove inadequate. To overcome these challenges, we propose an innovative fully fuzzy-based framework using LR flat fuzzy numbers. This framework allows for more… More >

Muhammad Amad Sarwar^1,*, Yuezheng Gong¹, Sarah A. Alzakari², Amel Ali Alhussan²

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.3, pp. 3523-3555, 2025, DOI:10.32604/cmes.2025.066356 - 30 June 2025

Abstract Global security threats have motivated organizations to adopt robust and reliable security systems to ensure the safety of individuals and assets. Biometric authentication systems offer a strong solution. However, choosing the best security system requires a structured decision-making framework, especially in complex scenarios involving multiple criteria. To address this problem, we develop a novel quantum spherical fuzzy technique for order preference by similarity to ideal solution (QSF-TOPSIS) methodology, integrating quantum mechanics principles and fuzzy theory. The proposed approach enhances decision-making accuracy, handles uncertainty, and incorporates criteria relationships. Criteria weights are determined using spherical fuzzy sets,… More >

Yushan Yin¹, Witold Pedrycz^1,2, Zhiwu Li^1,*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 623-650, 2024, DOI:10.32604/cmc.2024.048787 - 25 April 2024

Abstract Utilizing granular computing to enhance artificial neural network architecture, a new type of network emerges—the granular neural network (GNN). GNNs offer distinct advantages over their traditional counterparts: The ability to process both numerical and granular data, leading to improved interpretability. This paper proposes a novel design method for constructing GNNs, drawing inspiration from existing interval-valued neural networks built upon NNNs. However, unlike the proposed algorithm in this work, which employs interval values or triangular fuzzy numbers for connections, existing methods rely on a pre-defined numerical network. This new method utilizes a uniform distribution of information More >

Mani Parimala¹, Karthikeyan Prakash¹, Ashraf Al-Quran^2,*, Muhammad Riaz³, Saeid Jafari⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 1095-1118, 2024, DOI:10.32604/cmes.2023.031193 - 30 December 2023

Abstract The idea of linear Diophantine fuzzy set (LDFS) theory with its control parameters is a strong model for machine learning and optimization under uncertainty. The activity times in the critical path method (CPM) representation procedures approach are initially static, but in the Project Evaluation and Review Technique (PERT) approach, they are probabilistic. This study proposes a novel way of project review and assessment methodology for a project network in a linear Diophantine fuzzy (LDF) environment. The LDF expected task time, LDF variance, LDF critical path, and LDF total expected time for determining the project network… More > Graphic Abstract

A. Thiruppathi^*, C. K. Kirubhashankar

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2253-2266, 2023, DOI:10.32604/iasc.2023.033870 - 05 January 2023

Abstract The output of the fuzzy set is reduced by one for the defuzzification procedure. It is employed to provide a comprehensible outcome from a fuzzy inference process. This page provides further information about the defuzzification approach for quadrilateral fuzzy numbers, which may be used to convert them into discrete values. Defuzzification demonstrates how useful fuzzy ranking systems can be. Our major purpose is to develop a new ranking method for generalized quadrilateral fuzzy numbers. The primary objective of the research is to provide a novel approach to the accurate evaluation of various kinds of fuzzy… More >

Alhanouf Alburaikan¹, Hamiden Abd El-Wahed Khalifa^1,2, Pavan Kumar^3,*, Seyedali Mirjalili^4,6, Ibrahim Mekawy⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 1943-1956, 2023, DOI:10.32604/cmes.2022.021815 - 20 September 2022

Abstract In this article, mathematical modeling for the evaluation of reliability is studied using two methods. One of the methods, is developed based on possibility theory. The performance of the reliability of the system is of prime concern. In view of this, the outcomes for the failure are required to evaluate with utmost care. In possibility theory, the reliability information data determined from decision-making experts are subjective. The same method is also related to the survival possibilities as against the survival probabilities. The other method is the one that is developed using the concept of approximation More >

Deepak Sukheja¹, Javaid Ahmad Shah², G. Madhu³, K. Sandeep Kautish⁴, Fahad A. Alghamdi⁵, Ibrahim. S. Yahia^6,7,8, El-Sayed M. El-Kenawy^9,10, Ali Wagdy Mohamed^11,12,*

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4595-4609, 2022, DOI:10.32604/cmc.2022.029122 - 28 July 2022

Abstract Efficient decision-making remains an open challenge in the research community, and many researchers are working to improve accuracy through the use of various computational techniques. In this case, the fuzzification and defuzzification processes can be very useful. Defuzzification is an effective process to get a single number from the output of a fuzzy set. Considering defuzzification as a center point of this research paper, to analyze and understand the effect of different types of vehicles according to their performance. In this paper, the multi-criteria decision-making (MCDM) process under uncertainty and defuzzification is discussed by using… More >

Yi Liang^1,2, Haichao Wang^3,*, Wei-Chiang Hong⁴

Energy Engineering, Vol.119, No.1, pp. 163-188, 2022, DOI:10.32604/EE.2022.017396 - 22 November 2021

Abstract Photovoltaics (PV) has been combined with many other industries, such as agriculture. But there are many problems for the sustainability of PV agriculture. Timely and accurate sustainability evaluation of modern photovoltaic agriculture is of great significance for accelerating the sustainable development of modern photovoltaic agriculture. In order to improve the timeliness and accuracy of evaluation, this paper proposes an evaluation model based on interval type-2 Fuzzy AHP-TOPSIS and least squares support vector machine optimized by fireworks algorithm. Firstly, the criteria system of modern photovoltaic agriculture sustainability is constructed from three dimensions including technology sustainability, economic… More >

Raman Kumar Goyal¹, Jaskirat Singh¹, Nidhi Kalra¹, Anshu Parashar^1,*, Gagan Singla², Sakshi Kaushal²

Computer Systems Science and Engineering, Vol.41, No.1, pp. 157-170, 2022, DOI:10.32604/csse.2022.018962 - 08 October 2021

Abstract This paper proposes anoptimal fuzzy-based model for obtaining crisp priorities for Fuzzy-AHP comparison matrices. Crisp judgments cannot be given for real-life situations, as most of these include some level of fuzziness and complexity. In these situations, judgments are represented by the set of fuzzy numbers. Most of the fuzzy optimization models derive crisp priorities for judgments represented with Triangular Fuzzy Numbers (TFNs) only. They do not work for other types of Triangular Shaped Fuzzy Numbers (TSFNs) and Trapezoidal Fuzzy Numbers (TrFNs). To overcome this problem, a sum of squared error (SSE) based optimization model is… More >

Jie Ling^1,2, Xinmei Li^1,2, Mingwei Lin^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 117-148, 2021, DOI:10.32604/cmes.2021.016356 - 24 August 2021

Abstract During the COVID-19 outbreak, the use of single-use medical supplies increased significantly. It is essential to select suitable sites for establishing medical waste treatment stations. It is a big challenge to solve the medical waste treatment station selection problem due to some conflicting factors. This paper proposes a multi-attribute decision-making (MADM) method based on the partitioned Maclaurin symmetric mean (PMSM) operator. For the medical waste treatment station selection problem, the factors or attributes (these two terms can be interchanged.) in the same clusters are closely related, and the attributes in different clusters have no relationships.… More >