Article
Computer Science, Artificial Intelligence
Mohamed Shalaby, Ayman Mohammed, Sally Kassem
Summary: This study proposes three supervised FCM techniques for clustering phase at reduced cost via centroids initialization phase. The results show that the proposed three initialization techniques are efficient in terms of solution quality and computational cost.
INTERNATIONAL ARAB JOURNAL OF INFORMATION TECHNOLOGY
(2021)
Article
Computer Science, Artificial Intelligence
Xiaowei Zhao, Feiping Nie, Rong Wang, Xuelong Li
Summary: This paper proposes a novel fuzzy K-Means clustering model for conducting clustering tasks on a flexible manifold. The model performs fuzzy clustering based on shrunk patterns with desired manifold structure, and integrates the learning of shrunk patterns and the learning of membership degree into a unified framework. Experimental results demonstrate the feasibility and effectiveness of the proposed clustering algorithms.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2023)
Article
Computer Science, Artificial Intelligence
Pankaj Gupta, Mukesh Kumar Mehlawat, Anisha Khaitan, Witold Pedrycz
Summary: Shared transportation involves vehicles, drivers, and customers, and the interactions among them can have long-term impacts on the business. Machine learning techniques have been found to significantly improve results when integrated with existing models. The availability of extensive unstructured textual data has led to research in text generation and mining. Understanding and analyzing such data has become crucial for modern commercial applications.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2021)
Article
Automation & Control Systems
Jianhua Xiao, Tao Zhang, Jingguo Du, Xingyi Zhang
Summary: This article proposes a heuristic algorithm, EMRG-HA, to tackle large-scale vehicle routing problems. By utilizing the divide and conquer framework and evolutionary multiobjective route grouping method, the algorithm shows superior performance in solving large-scale CVRPs and outperforms eight existing algorithms in terms of both computational efficiency and solution quality in experimental evaluations.
IEEE TRANSACTIONS ON CYBERNETICS
(2021)
Review
Computer Science, Information Systems
Seyed Mahdi Miraftabzadeh, Cristian Giovanni Colombo, Michela Longo, Federica Foiadelli
Summary: As power systems evolve and become more complex with the integration of renewable energy sources, distributed generation, and electric vehicles, clustering algorithms such as K-means are becoming crucial tools for analyzing and optimizing these systems. This paper provides a comprehensive review of the application of K-means clustering and alternative methods in modern power systems, emphasizing the wide-ranging applications and the exponential growth in publications using clustering algorithms in this field. The study also explores the limitations and advantages of K-means and introduces alternative clustering algorithms that can be used in power system studies. This research highlights the importance for professionals to understand various clustering methods and incorporate the most suitable ones into their studies.
Article
Computer Science, Artificial Intelligence
Mariem Belhor, Adnen El-Amraoui, Abderrazak Jemai, Francois Delmotte
Summary: This paper proposes a bi-objective mathematical model for the home health care routing and scheduling problem, and presents three solution approaches. The results of the study demonstrate the effectiveness and suitability of these approaches.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Multidisciplinary Sciences
Juan Carlos Figueroa-Garcia, Jhoan Sebastian Tenjo-Garcia, Carlos Franco
Summary: This study proposes a method that uses third-party information from experts to represent uncertain costs/demands as fuzzy numbers, solving vehicle routing problems through iterative-integer programming and a global satisfaction degree, with experiments confirming convergence regardless of initial parameter selection.
Article
Computer Science, Artificial Intelligence
Zeynep Aydinalp Birecik, Dogan Oezgen
Summary: The green capacitated vehicle routing problem (GCVRP) has become a significant research topic due to the increasing global climate issues. This study presents an interactive fuzzy approach to solve GCVRP with imprecise travel time and supplier demands. The proposed model considers two objective functions: minimum fuel consumption and maximum green score. The model is applied to an automotive company in Turkey and provides a suggestion for vehicle routing.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Ioan-Daniel Borlea, Radu-Emil Precup, Alexandra-Bianca Borlea, Daniel Iercan
Summary: This paper introduces the novel Unified Form (UF) clustering algorithm and the Partitional Implementation of Unified Form (PIUF) algorithm, aiming to address the challenges of processing large datasets and sequential data processing. These algorithms are implemented and validated in the BigTim platform and can be applied to other data processing platforms.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Computer Science, Theory & Methods
Claire Mathieu, Hang Zhou
Summary: We propose a PTAS for solving the unit demand capacitated vehicle routing problem (CVRP) on trees, covering all possible tour capacities. The same approach can be extended to the splittable CVRP.
ACM TRANSACTIONS ON ALGORITHMS
(2023)
Article
Computer Science, Artificial Intelligence
Yuzhou Zhang, Yi Mei, Haiqi Zhang, Qinghua Cai, Haifeng Wu
Summary: In this article, a new divide-and-conquer strategy is proposed for solving Large Scale MDCARP, which introduces a restricted global optimization stage and a problem-specific Task Moving among Sub-problems process. By incorporating these into the RoCaSH algorithm, the resultant RoCaSH2 algorithm outperforms state-of-the-art algorithms in terms of efficiency and effectiveness on a wide range of instances.
IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE
(2023)
Article
Computer Science, Artificial Intelligence
Xiyang Yang, Fusheng Yu, Witold Pedrycz
Summary: Type-2 fuzzy sets are efficient in handling uncertainties and noisy observations. The characteristic-based type-2 fuzzy clustering algorithm proposed in this article optimizes parameter derivation formulas, enhances clustering efficiency, and effectively detects noise while assigning suitable membership degrees to data.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2021)
Article
Mathematics
Karim El Moutaouakil, Vasile Palade, Safaa Safouan, Anas Charroud
Summary: Soft computing models based on fuzzy or probabilistic approaches provide decision system makers with the ability to handle imprecise and incomplete information. A new measurement method that combines fuzzy and probabilistic notions has been proposed, which evaluates both the degree of membership and the frequency of objects/events. This method has shown improvements in performance measures for both clustering and image compression tasks.
Article
Management
Dorian Dumez, Christian Tilk, Stefan Irnich, Fabien Lehuede, Katharina Olkis, Olivier Peton
Summary: This paper addresses the logistic challenges in last-mile collection and delivery services and proposes a mathematical model and heuristic algorithm to solve the problem.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Computer Science, Information Systems
Sampriti Soor, Aditya Challa, Sravan Danda, B. S. Daya Sagar, Laurent Najman
Summary: This article introduces a modified algorithm, the iterated watersheds, based on K-Means, to address the clustering problem with connectivity constraints. Through experiments on toy examples and real-world applications, it is found that iterated watersheds outperforms traditional methods in tasks such as image segmentation and road network optimization.
IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTING
(2021)
Article
Transportation Science & Technology
Elvezia M. Cepolina, Alessandro Farina, Catherine Holloway, Nick Tyler
TRANSPORTATION PLANNING AND TECHNOLOGY
(2015)
Article
Transportation
Elvezia M. Cepolina, Alessandro Farina
EUROPEAN TRANSPORT RESEARCH REVIEW
(2015)
Article
Engineering, Civil
Elvezia M. Cepolina
FIRE SAFETY JOURNAL
(2009)
Article
Transportation Science & Technology
Elvezia M. Cepolina, Alessandro Farina
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2012)
Article
Transportation
Elvezia M. Cepolina, Alessandro Farina
EUROPEAN TRANSPORT RESEARCH REVIEW
(2014)
Article
Computer Science, Interdisciplinary Applications
Ilaria Giusti, Elvezia Maria Cepolina, Edoardo Cangialosi, Donato Aquaro, Gabriella Caroti, Andrea Piemonte
COMPUTERS & INDUSTRIAL ENGINEERING
(2019)
Proceedings Paper
Pediatrics
Elvezia M. Cepolina, Alessandro Farina
SIDT SCIENTIFIC SEMINAR 2013
(2015)
Article
Engineering, Civil
EM Cepolina
CIVIL ENGINEERING AND ENVIRONMENTAL SYSTEMS
(2005)
Article
Transportation Science & Technology
EA Cepolina, N Tyler
TRANSPORTATION PLANNING AND TECHNOLOGY
(2004)
Article
Psychology, Applied
Elvezia M. Cepolina, Federico Menichini, Paloma Gonzalez Rojas
TRANSPORTATION RESEARCH PART F-TRAFFIC PSYCHOLOGY AND BEHAVIOUR
(2018)
Article
Transportation Science & Technology
Rezia Molfino, Matteo Zoppi, Giovanni Gerardo Muscolo, Elvezia M. Cepolina, Alessandro Farina, Fawzi Nashashibi, Evangeline Pollard, Jose Antonio Dominguez
INTERNATIONAL JOURNAL OF ELECTRIC AND HYBRID VEHICLES
(2015)