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University of Technology of Troyes, France
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30 Papers

A Hybrid Genetic and Simulation Annealing Approach for a Multi-period Bid Generation Problem in Carrier Collaboration

Topics: Optimization; Management Sciences; Industrial Engineering; Scheduling; Routing; Logistics; OR in Transportation

Authors: Elham Mamaghani , Haoxun Chen and Christian Prins

Affiliation: Industrial Systems Optimization Laboratory, Charles Delaunay Institute and UMR CNRS 6281, University of Technology of Troyes, Troyes 10004 and France

Digital Object Identifier: 10.5220/0007369203070314

Proceedings of ICORES 2019, ISBN: 978-989-758-352-0

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In this article, a new vehicle routing problem appeared in carrier collaboration via a combinatorial auction (CA) is studied. A carrier with reserved requests wants to determine within a time horizon of multi periods (days) which requests to serve among a set of selective requests open for bid of the auction to maximize its profit. In each period, the carrier has a set of reserved requests that must be served by the carrier itself. Each request is specified by a pair of pickup and delivery locations, a quantity, and two time windows for pickup and delivery respectively. The objective of the carrier is to determine which selective requests may be served in each period in addition of its reserved requests and determine optimal routes to serve the reserved and selective requests to maximize its total profit. For this NP-hard problem, a mixed-integer linear programming model is formulated and a genetic algorithm combined with simulated annealing is proposed. The algorithm is evaluated on instances with 6 to 100 requests. The computational results show this algorithm significantly outperform CPLEX solver, not only in computation time but also in solution quality.
Collapse Button Related Ontology Subjects/Areas/Topics (18)
Applications

Knowledge-Based Systems

OR in Transportation

Artificial Intelligence

Logistics

Pattern Recognition

e-Business

Management Sciences

Routing

Enterprise Information Systems

Methodologies and Technologies

Scheduling

Industrial Engineering

Operational Research

Software Engineering

Knowledge Discovery and Information Retrieval

Optimization

Symbolic Systems

Assist the Sustainable Development within Industries through the Territorial Knowledge Ontology

Topics: Knowledge Management Projects; KM Strategies and Implementations ; Management and Organisational Issues in Information Systems

Authors: Amer Ezoji and Nada Matta

Affiliation: ICD/ TECH-CICO, University of Technology of Troyes, 12 Rue Marie Curie, Troyes and France

Digital Object Identifier: 10.5220/0008165201020112

Proceedings of KMIS 2019, ISBN: 978-989-758-382-7

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Studying of territory as the main dimension of sustainability impact in the industrial activities and decision makers’ information when considering the sustainability in their activities. Therefore, exploring of territorial knowledge in order to integrate into industries activates is needed. So, this research is proposed a descriptive ontology for territorial knowledge (DOTK) which make explicit the knowledge of actors within industries about the sustainable development goal. Also, implementation of this ontology to a real case is proved that it can identify the intangible and tangible resources of territory for sustainability. Moreover, a semantic graph is proposed which shows the relationships between entities of DOTK ontology. Final validation of DOTK ontology is performed by the interview with the organizations of sustainable development implementation.
Collapse Button Related Ontology Subjects/Areas/Topics (6)
Artificial Intelligence

Knowledge Management and Information Sharing

Knowledge-Based Systems

KM Strategies and Implementations

Knowledge Management Projects

Symbolic Systems

Modeling and Evaluation of a City Logistics System with Freight Buses

Topics: Industrial Engineering; Routing; Logistics; OR in Transportation

Authors: Zheng Chang , Haoxun Chen and Farouk Yalaoui

Affiliation: ICD-LOSI, UMR CNRS 6281, University of Technology of Troyes, Troyes and France

Digital Object Identifier: 10.5220/0007362502920298

Proceedings of ICORES 2019, ISBN: 978-989-758-352-0

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Freight bus is a new public transportation means for city logistics, and each freight bus can deliver and pick up goods at each customer/supplier location it passes. In this paper, we study the route planning problem of freight buses in an urban distribution system. Since each freight bus makes a tour visiting a set of pickup/delivery locations once at every given time interval in each day following a fixed route, the route planning problem can be considered a new variant of periodic vehicle routing problem with pickup and delivery. In order to solve the problem, a Mixed-Integer Linear Programming (MILP) model is formulated. Based on the model, we compare a distribution system with freight buses with that without freight bus. Preliminary numerical results on randomly generated instances show that the system with freight buses can significantly reduce transportation costs compared with the system without freight buses.
Collapse Button Related Ontology Subjects/Areas/Topics (11)
Applications

Logistics

Pattern Recognition

e-Business

Methodologies and Technologies

Routing

Enterprise Information Systems

Operational Research

Software Engineering
Industrial Engineering

OR in Transportation

Rethinking Strategies of Hackathons to Increase Team’s Creativity: Findings of a Qualitative Research

Topics: Communication, Collaboration and Information Sharing; Knowledge Management Projects

Authors: Nelson Tenório 1 , Gisele Lourenço 2 , Mariana Oliveira 2 , Steffi Becker 2 , Fabrício Bernardelli 2 , Hassan Atifi 3 and Nada Matta 3

Affiliations: 1 Cesumar Institute of Science, Technology and Innovation (ICETI), UniCesumar, Maringá, Paraná and Brazil , 2 Masters’Program in Knowledge Management, UniCesumar, Maringá, Paraná and Brazil , 3 Department of Computer Science, University of Technology of Troyes, Troyes and France

Digital Object Identifier: 10.5220/0008164300920101

Proceedings of KMIS 2019, ISBN: 978-989-758-382-7

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Hackathons are events that have become increasingly common around the world. This kind of event, described as a programming marathon, is based on problem-solving that can go beyond the technological boundary. This paper presents the findings of an international hackathon to aid its organizers to rethink their strategies to improve the development of the team’s creativity to solve the challenge proposed. The paper summarizes qualitative research based on interviews and observations which point out that the organizers should consider strategies to improve knowledge application, resolving conflicts, individual learning, and experienced emotions, during pre-hackathon as well as post-hackathon events. Our findings could leverage the innovation, creativity, and knowledge sharing and creation within hackathons.
Collapse Button Related Ontology Subjects/Areas/Topics (6)
Artificial Intelligence

Knowledge Management and Information Sharing

Knowledge-Based Systems

Communication, Collaboration and Information Sharing

Knowledge Management Projects

Symbolic Systems

Abnormal Events Detection for Infrastructure Security using Key Metrics

Topics: Video Analysis; Classification; Signal Processing

Authors: Van-Khoa Le , Edith Grall-Maes and Pierre Beauseroy

Affiliation: Troyes University of Technology, France

Digital Object Identifier: 10.5220/0006552102840290

Proceedings of ICPRAM 2018, ISBN: 978-989-758-276-9

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This paper presents a detection process which utilizes various sensors (camera, card readers, movement detector) for detecting automatically abnormal events. The detection process strengthens current security systems to identify attackers in the context of building and office. Key metrics are proposed to describe people’s behavior in critical zones of the building. They are built using measures from the sensors, which provide information about the person, the position, and the instant. These metrics are used to classify abnormal behaviors from regular ones, based on a statistical classifier. This technique is tested on both simulated data and real data, in which an attacking scenario was prepared by security experts. Results show that abnormal events from the scenario have been successfully detected. The experiments demonstrate that the proposed key metrics are relevant and the proposed detection scheme is appropriate for infrastructure surveillance.
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Applications

Computer Vision, Visualization and Computer Graphics

Signal Processing

Cardiovascular Imaging and Cardiography

Health Engineering and Technology Applications

Software Engineering

Cardiovascular Technologies

Image and Video Analysis

Theory and Methods

Classification

Pattern Recognition

Video Analysis

How Territorial Knowledge Effects on the Sustainable Development within Companies

Topics: Knowledge Management Projects; KM Strategies and Implementations

Authors: Amer Ezoji and Nada Matta

Affiliation: ICD/ TECH-CICO, University of Technology of Troyes,12 Rue Marie Curie, Troyes and France

Digital Object Identifier: 10.5220/0006893401110119

Proceedings of KMIS 2018, ISBN: 978-989-758-330-8

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Nowadays sustainability is issued to industries in order to integrate it into their activities for sustainable development. Studying of territorial resources impact on industrial activities and decision makers’ information when considering sustainability. The aim is to enhance the knowledge of actors in the industries in relation to territorial resource through sustainable objective. Moreover, considering how this knowledge can help to the different level of industry in regard to value creation for human and decision making. This consideration is done by categorizing of territorial knowledge and linking them with other classes and industrial organization.
Collapse Button Related Ontology Subjects/Areas/Topics (6)
Artificial Intelligence

Knowledge Management and Information Sharing

Knowledge-Based Systems

KM Strategies and Implementations

Knowledge Management Projects

Symbolic Systems

Investigating Knowledge Management in the Software Industry: The Proof of Concept’s Findings of a Questionnaire Addressed to Small and Medium-sized Companies

Topic: KM Strategies and Implementations

Authors: Danieli Pinto 1 , Mariana Oliveira 1 , Flávio Bortolozzi 2 , Nada Matta 3 and Nelson Tenório 4

Affiliations: 1 Knowledge Management Master’s Program of UniCesumar, Av. Guedner, 1218, build 7, Maringá, Paraná and Brazil , 2 Knowledge Management Master’s Program of UniCesumar, Av. Guedner, 1218, build 7, Maringá, Paraná, Brazil, Institute Cesumar of Science, Technology, and Innovation, Av. Guedner, 1218, build 11, Maringá, Paraná and Brazil , 3 University of Troyes, 12 rue Marie Curie, Troyes and France , 4 Knowledge Management Master’s Program of UniCesumar, Av. Guedner, 1218, build 7, Maringá, Paraná, Brazil, Institute Cesumar of Science, Technology, and Innovation, Av. Guedner, 1218, build 11, Maringá, Paraná, Brazil, University of Troyes, 12 rue Marie Curie, Troyes and France

Digital Object Identifier: 10.5220/0006925000730082

Proceedings of KMIS 2018, ISBN: 978-989-758-330-8

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The software industry is dynamic and complex, so they need to use the knowledge to excel in a highly competitive market. Thus, the knowledge well managed brings the organization a sustainable and competitive advantage. Knowledge Management (KM) processes can avoid knowledge lost since they provide knowledge flow for the whole organization. These processes are supported by practices and tools promoting the creation, retention, and dissemination of the knowledge within the organizational environment. The objective of this study was to validate, through a proof of concept (POC), a questionnaire to investigate the processes, practices, and tools of KM in SME-Soft. The questionnaire was evaluated by fifty-one professionals and KM experts from the software industry. Our findings point out that the questionnaire is suitable for the software industry.
Collapse Button Related Ontology Subjects/Areas/Topics (5)
Artificial Intelligence

Knowledge Management and Information Sharing

Symbolic Systems
KM Strategies and Implementations

Knowledge-Based Systems

Towards an Exploration of Several Dimensions in Learning: Application on Crisis Management

Topics: Communication, Collaboration and Information Sharing; Tools and Technology for Knowledge Management; Knowledge Management Projects; Learning Organization & Organizational Learning

Authors: Sammy Teffali , Nada Matta and Eric Châtelet

Affiliation: Université de Technologie de Troyes, 12 rue Marie Curie, 10300 Troyes and France

Digital Object Identifier: 10.5220/0006920001530160

Proceedings of KMIS 2018, ISBN: 978-989-758-330-8

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A crisis is a complex situation, which actors have some difficulties to manage it. They are under stress to deal with problems that they cannot predict consequences. The human conditions (familial and life) and, the influence of the environment (politic, economic, media) pushes the actors to lose control of the crisis situation. The question we face in this paper is: “is it possible to predict stress impact situations based on experience feedback?” “Is it possible to use this type of prediction for learning?” Our main hypothesis to represent experience feedback in a situation prediction in order to show negative consequences and correctness actions is taken account. Fuzzy theory concept is used in prediction in order to generate several situations and allow learners to explore different options.
Collapse Button Related Ontology Subjects/Areas/Topics (8)
Artificial Intelligence

Knowledge Management Projects

Symbolic Systems

Communication, Collaboration and Information Sharing

Knowledge-Based Systems

Tools and Technology for Knowledge Management
Knowledge Management and Information Sharing

Learning Organization & Organizational Learning

Definition of Experience Feedback Sheet for Eco-design

Topics: Communication, Collaboration and Information Sharing; Knowledge Management Projects; Organizational Memories

Authors: Nada Matta 1 , Carlos Delagado 1 , Tatiana Reyes 1 and Guillaume Jouanne 2

Affiliations: 1 University of Technology of Troyes, France , 2 Altermaker, France

Digital Object Identifier: 10.5220/0006488501010107

Proceedings of KMIS 2017, ISBN: 978-989-758-273-8

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In this paper, we propose a Knowledge to use experience feedback techniques in order to keep track of eco-design decisions. The integration of eco-design in industries is becoming more and more considered as a necessary condition of Sustainable development. Even sustainable rules become to be defined as norms, but the application of these rules in design still difficult. Firstly, eco-design criteria are extracted from documents in order to help the definition of experience feedback sheets main points. CommonKADS generic models are also used in order to define adequate sheets to reasoning and task types linked to eco-design phases.
Collapse Button Related Ontology Subjects/Areas/Topics (7)
Artificial Intelligence

Knowledge Management Projects

Organizational Memories

Communication, Collaboration and Information Sharing

Knowledge-Based Systems

Symbolic Systems
Knowledge Management and Information Sharing

Linear Discriminant Analysis based on Fast Approximate SVD

Topics: Classification; Feature Selection and Extraction; ICA, PCA, CCA and other Linear Models

Authors: Nassara Elhadji Ille Gado , Edith Grall-Maës and Malika Kharouf

Affiliation: University of Champagne / University of Technology of Troyes, France

Digital Object Identifier: 10.5220/0006148603590365

Proceedings of ICPRAM 2017, ISBN: 978-989-758-222-6

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We present an approach for performing linear discriminant analysis (LDA) in the contemporary challenging context of high dimensionality. The projection matrix of LDA is usually obtained by simultaneously maximizing the between-class covariance and minimizing the within-class covariance. However it involves matrix eigendecomposition which is computationally expensive in both time and memory requirement when the number of samples and the number of features are large. To deal with this complexity, we propose to use a recent dimension reduction method. The technique is based on fast approximate singular value decomposition (SVD) which has deep connections with low-rank approximation of the data matrix. The proposed approach, appSVD+LDA, consists of two stages. The first stage leads to a set of artificial features based on the original data. The second stage is the classical LDA. The foundation of our approach is presented and its performances in term of accuracy and computation time in comparison with some state-of-the-art techniques are provided for different real data sets.
Collapse Button Related Ontology Subjects/Areas/Topics (5)
Classification

ICA, PCA, CCA and other Linear Models

Theory and Methods
Feature Selection and Extraction

Pattern Recognition

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