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Опубліковано: 6 вересня 2023

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Статті в журналах з теми "Multi agent system-Supplier selection"

1

Yang, Chang Hui. "Supplier Selection of Multi-Agent Logistic System." Key Engineering Materials 467-469 (February 2011): 614–19. http://dx.doi.org/10.4028/www.scientific.net/kem.467-469.614.

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Choosing supplier with better quick response ability becomes more and more important. In this paper, the criterion of evaluating supplier is put forward and a method of evaluating supplier is introduced. To improve the efficiency of selecting supplier, a multi-agent system of supplier selection based on evaluating supplier is developed. Recurring to the supplier’s related data collected by data-mining agent from external web-server, the weights of criteria can be confirmed. And using the system, the supplier with better QRA can be selected based on the measuring results.
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2

Jahani, Alireza, Masrah Azrifah Azmi Murad, Md Nasir bin Sulaiman, and Mohd Hasan Selamat. "An agent-based supplier selection framework." Strategic Outsourcing: An International Journal 8, no. 2/3 (June 15, 2015): 180–205. http://dx.doi.org/10.1108/so-01-2015-0003.

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Purpose – The purpose of this paper is to propose an approach that integrates three complementary perspectives, multi-agent systems, fuzzy logic and case-based reasoning. Unsatisfied customers, information overload and high uncertainty are the main challenges that are faced by today’s supply chains. In addition, a few existing agent-based approaches are tied to real-world supply chain functions like supplier selection. These approaches are static and do not adequately take the qualitative and quantitative factors into consideration. Therefore, an agent-based framework is needed to address these issues. Design/methodology/approach – The proposed approach integrates three complementary perspectives, multi-agent systems, fuzzy logic and case-based reasoning, as a common framework. These perspectives were rarely used together as a common framework in previous studies. Furthermore, an exploratory case study in an office furniture company is undertaken to illustrate the value of the framework. Findings – The proposed agent-based framework evaluates supply offers based on customers’ preferences, recommends alternative products in the case of stock-out and provides a collaborative environment among agents who represent different supply chain entities. The proposed fuzzy case-based reasoning (F-CBR) approach reduces the information overload by organizing them into the relevant cases that causes less overall search between cases. In addition, its fuzzy aspect addresses the high uncertainty of supply chains, especially when there are different customers’ orders with different preferences. Research limitations/implications – The present study does not include the functions of inventory management and negotiation between agents. Furthermore, only the case description and case retrieval phases of the case-based reasoning approach are investigated, and the remaining phases like case retaining, case reusing and case revising are not included in the scope of this paper. Originality/value – This framework balances the interests of different supply chain structural elements where each of them is represented by a specific agent for better collaboration, decision-making and problem-solving in a multi-agent environment. In addition, the supplier selection and order gathering mechanisms are developed based on customers’ orders.
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3

Changhui Yang. "Supplier Selection Mechanism of Logistic Enterprise based on Multi-Agent System." International Journal of Advancements in Computing Technology 4, no. 16 (September 30, 2012): 437–44. http://dx.doi.org/10.4156/ijact.vol4.issue16.51.

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4

Li, Jinghua, Miaomiao Sun, Duanfeng Han, Xiaoyuan Wu, Boxin Yang, Xuezhang Mao, and Qinghua Zhou. "Semantic multi-agent system to assist business integration: An application on supplier selection for shipbuilding yards." Computers in Industry 96 (April 2018): 10–26. http://dx.doi.org/10.1016/j.compind.2018.01.001.

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5

Kumar, Bimal Aklesh, and Priya Mohite. "Cognitive Trust Model for B2B E-Market." International Journal of E-Business Research 11, no. 4 (October 2015): 32–46. http://dx.doi.org/10.4018/ijebr.2015100103.

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In recent years, B2B E-Market has received widespread amount of research attention in the field of electronic commerce. As majority of companies are investing huge amount of money to build the infrastructure for e-collaboration. Selecting suitable trading partners in an e-market still remains a huge challenge, as the selection of supplier depends not only on cost but on other factors such as reputation, satisfaction and trust. Trust is regarded as one of the most important factors for success and to ensure customers repeat trading. One of the major challenges faced by both research and industry is to measure trustworthiness of a supplier in an e-market place. This paper proposes a cognition based model to measure trustworthiness of a supplier. The proposed model with its implementation using multi-agent systems is described in detail. Finally empirical evaluation is carried out to validate the system and future direction for research in this area.
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6

Musumba, George Wamamu, and Patrick Kanyi Wamuyu. "Virtual Enterprise as a Multi Agent System." International Journal of Agent Technologies and Systems 8, no. 1 (January 2016): 46–68. http://dx.doi.org/10.4018/ijats.2016010103.

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This article describes changing customer demands require that enterprises mobilize their resources to quickly develop a suitable product. This is achievable if competing enterprises collaborate to deliver the product. Each of them brings their expertise into the collaboration. This collaboration where each enterprise brings in its core competency is referred to as a virtual enterprise (VE). A construction project is implemented by a team of professionals and an alliance of companies that is formed by consultants who evaluate contractors for specific project tasks. Partners can be represented as multiple agents. Prior evidence of multi-agent system (MAS) model that facilitates formation of VEs is lacking. VE MAS ontology has been designed and used in agent interactions. The model can be used in evaluation and selection process of partners. Delegation of the process to the model, gives partners time to implement the tasks. Partner evaluation and selection problem for building construction projects is solvable if pragmatic scientific approaches are employed with appropriate mathematical models. This article proposed a VE model for evaluating and selecting right partners for building construction projects. The model was used to demonstrate the choice of the most preferred partner. Researchers have not evaluated this model but propose that once in place, it can evaluated against manual selection of potential partners using similar parameters by examining the closeness of the output.
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Yu, Chunxia, and T. N. Wong. "A multi-agent architecture for multi-product supplier selection in consideration of the synergy between products." International Journal of Production Research 53, no. 20 (February 16, 2015): 6059–82. http://dx.doi.org/10.1080/00207543.2015.1010745.

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Yu, Chunxia, T. N. Wong, and Zhi Li. "A hybrid multi-agent negotiation protocol supporting supplier selection for multiple products with synergy effect." International Journal of Production Research 55, no. 1 (May 25, 2016): 18–37. http://dx.doi.org/10.1080/00207543.2016.1189105.

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Han, Wei, Bing Zhang, Qianyi Wang, Jun Luo, Weizhi Ran, and Yang Xu. "A Multi-Agent Based Intelligent Training System for Unmanned Surface Vehicles." Applied Sciences 9, no. 6 (March 15, 2019): 1089. http://dx.doi.org/10.3390/app9061089.

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The modeling and design of multi-agent systems is imperative for applications in the evolving intelligence of unmanned systems. In this paper, we propose a multi-agent system design that is used to build a system for training a team of unmanned surface vehicles (USVs) where no historical data concerning the behavior is available. In this approach, agents are built as the physical controller of each USV and their cooperative decisions used for the USVs’ group coordination. To make our multi-agent system intelligently coordinate USVs, we built a multi-agent-based learning system. First, an agent-based data collection platform is deployed to gather competition data from agents’ observation for on-line learning tasks. Second, we design a genetic-based fuzzy rule training algorithm that is capable of optimizing agents’ coordination decisions in an accumulated manner. The simulation results of this study demonstrate that our proposed training approach is feasible and able to converge to a stable action selection policy towards efficient multi-USVs’ cooperative decision making.
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Ghadimi, Pezhman, Chao Wang, Ming K. Lim, and Cathal Heavey. "Intelligent sustainable supplier selection using multi-agent technology: Theory and application for Industry 4.0 supply chains." Computers & Industrial Engineering 127 (January 2019): 588–600. http://dx.doi.org/10.1016/j.cie.2018.10.050.

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Дисертації з теми "Multi agent system-Supplier selection"

1

Sturesson, Johan, and Mattias Sjöberg. "Situation assessment and role selection in the simulated RoboCup domain." Thesis, Blekinge Tekniska Högskola, Institutionen för programvaruteknik och datavetenskap, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-2827.

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In the recent world championships of the simulated RoboCup league the winning teams possessed low level behaviours, such as kick and pass, that were close to perfection. In order to improve a team's performance you will need, beside perfect low level behaviours, a good management of the team. We present a model for managing a team in the simulated RoboCup league. The model is based on techniques used by the recent winners in the league and allows you to get a well coordinated team of agents striving for a common goal. The model supports different formations in different situations, which contributes to a dynamic team play, where the players can adjust to their opponents and other factors like time left and goal difference. For example if the game is near the end and the team is loosing a more risky and aggressive tactic is chosen.
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2

Berglund, David, and Niklas Larsson. "Controlling a Hydraulic System using Reinforcement Learning : Implementation and validation of a DQN-agent on a hydraulic Multi-Chamber cylinder system." Thesis, Linköpings universitet, Fluida och mekatroniska system, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-177216.

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One of the largest energy losses in an excavator is the compensation loss. In a hydraulic load sensing system where one pump supplies multiple actuators, these compensation losses are inevitable. To minimize the compensation losses the use of a multi chamber cylinder can be used, which can control the load pressure by activate its chambers in different combinations and in turn minimize the compensation losses.  For this proposed architecture, the control of the multi chamber cylinder systems is not trivial. The possible states of the system, due to the number of combinations, makes conventional control, like a rule based strategy, unfeasible. Therefore, is the reinforcement learning a promising approach to find an optimal control.  A hydraulic system was modeled and validated against a physical one, as a base for the reinforcement learning to learn in simulation environment. A satisfactory model was achieved, accurately modeled the static behavior of the system but lacks some dynamics.  A Deep Q-Network agent was used which successfully managed to select optimal combinations for given loads when implemented in the physical test rig, even though the simulation model was not perfect.
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Younes, Walid. "Un système multi-agent pour la composition logicielle opportuniste en environnement ambiant et dynamique." Thesis, Toulouse 3, 2021. http://www.theses.fr/2021TOU30025.

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Les systèmes cyber-physiques et ambiants sont constitués d'appareils fixes ou mobiles reliés par des réseaux de communication. Ces appareils hébergent des composants logiciels qui fournissent des services et peuvent nécessiter d'autres services pour fonctionner. Ces composants logiciels sont généralement développés, installés et activés indépendamment les uns des autres et, avec la mobilité des utilisateurs et des appareils, ils peuvent apparaître ou disparaître avec une dynamique imprévisible. Ceci donne aux systèmes cyber-physiques et ambiants une nature ouverte et changeante. Les composants logiciels sont des briques que l'on peut assembler pour former des applications mais, dans un tel contexte de dynamique et d'ouverture, les assemblages de composants sont difficiles à concevoir, à maintenir et à adapter. Les applications sont utilisées par des humains qui sont donc au cœur de ces systèmes. L'intelligence ambiante vise à leur offrir un environnement personnalisé adapté à la situation, c'est-à-dire à fournir la bonne application au bon moment, en anticipant leurs besoins, qui peuvent aussi changer dans le temps. Pour répondre à ces problèmes, notre équipe explore une approche originale appelée "composition logicielle opportuniste" qui consiste à construire automatiquement des applications à la volée à partir des composants disponibles sur le moment dans l'environnement, sans s'appuyer sur des besoins explicites de l'utilisateur ni sur des plans d'assemblage prédéfinis. Ainsi, les applications émergent de l'environnement, en tirant parti des opportunités au fur et à mesure qu'elles se présentent. Cette thèse définit une architecture logicielle pour la composition logicielle opportuniste et propose un système intelligent, appelé "moteur" de composition opportuniste, afin de construire automatiquement des applications pertinentes, à la fois adaptées à l'utilisateur et à l'environnement ambiant. Le moteur de composition opportuniste détecte périodiquement les composants et leurs services présents dans l'environnement ambiant, construit des assemblages de composants et les propose à l'utilisateur. Il apprend automatiquement les préférences de l'utilisateur en fonction de la situation afin de maximiser ultérieurement sa satisfaction. L'apprentissage se fait en ligne par renforcement. Il est décentralisé au sein d'un système multi-agent dans lequel les agents interagissent via un protocole qui prend en charge la découverte et la sélection dynamique de services. Pour apprendre de l'utilisateur et pour l'utilisateur, ce dernier est mis dans la boucle. Ainsi, il garde le contrôle sur son environnement ambiant, et décide de la pertinence de l'application émergente avant qu'elle ne soit déployée. La solution a été implémentée et expérimentée. Elle fonctionne de manière couplée avec une interface qui décrit les applications émergentes à l'utilisateur et lui permet de les modifier. Les actions de l'utilisateur sur cette interface sont sources de feedback pour le moteur et servent à alimenter le mécanisme d'apprentissage par renforcement
Cyber-physical and ambient systems consist of fixed or mobile devices connected through communication networks. These devices host software components that provide services and may require other services to operate. These software components are usually developed, installed, and activated independently of each other and, with the mobility of users and devices, they may appear or disappear unpredictably. This gives cyber-physical and ambient systems an open and changing character. Software components are bricks that can be assembled to form applications. But, in such a dynamic and open context, component assemblies are difficult to design, maintain and adapt. Applications are used by humans who are at the heart of these systems. Ambient intelligence aims to offer them a personalized environment adapted to the situation, i.e. to provide the right application at the right time, anticipating their needs, which may also vary and evolve over time. To answer these problems, our team is exploring an original approach called "opportunistic software composition", which consists in automatically building applications on the fly from components currently available in the environment, without relying on explicit user needs or predefined assembly plans. In this way, applications emerge from the environment, taking advantage of opportunities as they arise. This thesis defines a software architecture for opportunistic software composition and proposes an intelligent system, called "opportunistic composition engine", in order to automatically build relevant applications, both adapted to the user and to the surrounding environment. The opportunistic composition engine periodically detects the components and their services that are present in the ambient environment, builds assemblies of components, and proposes them to the user. It automatically learns the user's preferences according to the situation in order to maximize user satisfaction over time. Learning is done online by reinforcement. It is decentralized within a multi-agent system in which agents interact via a protocol that supports dynamic service discovery and selection. To learn from and for the user, the latter is put in the loop. In this way, he keeps control over his ambient environment, and decides on the relevance of the emerging application before it is deployed. The solution has been implemented and tested. It works in conjunction with an interface that describes the emerging applications to the user and allows him to edit them. The user's actions on this interface are sources of feedback for the engine and serve as an input to the reinforcement learning mechanism
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4

Louati, Amine. "Une approche multi-agents pour la composition de services Web fondée sur la confiance et les réseaux sociaux." Thesis, Paris 9, 2015. http://www.theses.fr/2015PA090035/document.

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Dans cette thèse, nous nous intéressons aux problèmes de découverte, de sélection et de composition de services. L'objectif est de satisfaire une requête complexe d'un demandeur de services. Pour ce faire, nous proposons une approche multi-agents fondée sur la confiance et les réseaux sociaux. Nous définissions un modèle de confiance en tant que concept compositionnel formé de quatre composantes: une composante sociale, une composante d'expertise, une composante de recommandation et une composante de coopération. La composante sociale juge s'il est intéressant de suivre un fournisseur avant d'utiliser ses services. La composante d'expertise estime si un service se comporte bien et comme prévu. La composante de recommandation vérifie si un agent est pertinent ou pas et si l'on peut compter sur ses recommandations. La composante de coopération permet aux agents de décider avec qui interagir dans une composition de services. Nous proposons un algorithme distribué pour la découverte de services utilisant la confiance entre les agents ainsi que les systèmes de références dans les réseaux sociaux. Nous développons également une nouvelle méthode s'appuyant sur un modèle probabiliste pour inférer la confiance entre les agents non adjacents tout en tenant compte des rôles des agents intermédiaires. Finalement, nous présentons un processus original de formation de coalitions qui est incrémental, dynamique et recouvrant pour une composition de services dans les réseaux sociaux. Les résultats expérimentaux montrent que nos approches multi-agents sont efficaces, plus performants que les approches similaires existantes et peuvent offrir des résultats plus dignes de confiance à faible coût de communications
This thesis deals with service discovery, selection and composition problems. The aim is to fulfill a complex requester query. To do that, we propose a multi-agent approach based on trust and social networks. We define a trust model as a compositional concept that includes social, expert, recommender and cooperation-based component. The social-based component judges whether or not the provider is worthwhile pursuing before using his services. The expert-based component estimates whether or not the service behaves well and as expected. The recommender-based component checks whether or not an agent is reliable and if we can rely on its recommendations. The cooperation-based component allows agents to decide with whom to interact in a service composition. We propose a distributed algorithm for service discovery using trust between agents and referral systems in social networks. We also develop a new method based on a probabilistic model to infer trust between non adjacent agents while taking into account roles of intermediate agents. Finally, we present an original coalition formation process which is incremental, dynamic and overlapping for service composition in social networks. %In particular, our coalition formation process engaging self-interested agents is incremental, dynamic and overlapping. Experimental results show that our multi-agents approaches are efficient, outperforms existing similar ones and can deliver more trustworthy results at low cost of communications
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SCHRAMM, Fernando. "Modelo de seleção de fornecedores para compras públicas baseado em negociação multibilateral e multiaspecto." Universidade Federal de Pernambuco, 2013. https://repositorio.ufpe.br/handle/123456789/18967.

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Submitted by Caroline Falcao (caroline.rfalcao@ufpe.br) on 2017-06-01T18:14:47Z No. of bitstreams: 2 license_rdf: 811 bytes, checksum: e39d27027a6cc9cb039ad269a5db8e34 (MD5) Fernando TESE.pdf: 6232408 bytes, checksum: 2758b5fef89a3422ca1f59c9255a8e14 (MD5)
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A complexidade de um processo licitatório, o princípio da isonomia e a tentativa de obter a proposta mais vantajosa têm induzido a administração pública a adotar uma abordagem de seleção de fornecedores, onde o preço é o único aspecto considerado. Com o objetivo de apoiar este processo, esta tese propõe um modelo de seleção de fornecedores, baseado na legislação brasileira de licitação, que contempla uma etapa de negociação sobre múltiplos aspectos. O modelo estrutura o processo de compras de bens na administração pública em um fluxo de atividades: (i) captação das propostas; (ii) etapa de negociação; e (iii) homologação e adjudicação das propostas. A etapa de negociação consiste de um modelo de apoio à negociação multibilateral e multiaspecto, cuja estratégia adotada garanta ganhos mútuos máximos para as partes envolvidas. O modelo proposto é ilustrado por meio de um processo licitatório já finalizado. Através desta ilustração é possível verificar que o modelo agrega maior dinâmica a lei de licitações, pois as ofertas dos fornecedores são intervalos de valores em diferentes aspectos ao invés de uma oferta fixa e única apenas no aspecto preço. Verificou-se também que a proposta pode ser utilizada para apoiar processos de seleção de fornecedores de empresas do setor privado.
The complexity of bidding process, the equality principle and the attempt to obtain the most advantageous bid have led the government to adopt a selection supplier approach, in which the price is the only issue considered. In order to support this process, this thesis proposes a supplier selection model based on the Brazilian bidding law, which includes a negotiation stage on multiple issues. The model organizes the public bidding process in a flow of activities: (i) bids reception; (ii) negotiation stage; and (iii) approval and award of bids. The negotiation stage is developed as a model to support multi-bilateral and multi-issue negotiations, whose adopted strategy ensures joint maximum gains for the parties involved. The proposed model is illustrated through its application for a bidding process already concluded. This illustration showed that the model aggregates more dynamic to the bidding law since the suppliers bids are ranges of values in different issues instead of a single bid in the price issue only. It was verified that the proposal can be used to support suppliers selection processes in private sector companies.
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Chen, Yun-ju, and 陳韻如. "Multi-agent based Dynamic Supplier Selection System." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/33214769772297833460.

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Анотація:
碩士
國立成功大學
資訊管理研究所
95
Facing the trend of globalization, how to lower costs, improve profitability, and share knowledge through supply chain management in the competitive market is an important topic to the decision makers. Thus, selecting the appropriate manufacturers that fulfil enterprise’s demand is the first step to have a successful supply chain management. Good supplier’s relationship can be established through sharing information and cooperation. With the development of information science and technology, it is very urgent to solve the problem of how to utilize information technology to help enterprises choosing the correct supplier. The previous method of collecting data unilaterally has become impractical. Therefore, selecting suppliers would be more flexible and efficient through the multi-agent’s structure. This research presents a prototype of multi-agent-based system, which enables both parties to consult with each other flexibly. The buyer can choose the suitable supplier through this prototype to improve supplier selection decision procedure. Due to the dynamic environment, we analyze enterprise’s demand on the supplier, appoint the agent to go to the external supplier to seek the proper solution, use the mobile agent’s mobility and way of communication of multi-agent, and enable both parties to communicate dynamically constantly. This procedure makes the supplier selection fit better to reality. This research applies multi-agent’s technology on supplier selection question. At last, this research has found that multi-agent technology makes supplier selection procedure more flexible and efficient through some case studies.
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JAIN, VIPUL. "Hybrid approaches to model supplier related issues in a dynamic supply chain." Thesis, 2006. http://localhost:8080/iit/handle/2074/25489.

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8

Yang, Tsung-Hsien, and 楊宗憲. "An Intelligent Agent-Based System for Personalized Channel Selection in Multi-media Broadcasting Environments." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/75445491332222117823.

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Анотація:
碩士
國立屏東科技大學
資訊管理系
90
Abstract: It has been advocated to develop information appliances to provide ubiquitous Internet information access. With the invention of digital set-top-box, television is expected to become one of the most popular information appliances soon, due to the tremendous digital multi-media programmes it can broadcast. However, as in the World Wide Web, the available TV programmes and their correspondingly electronic information within the increasing digital channels lead to the problem of information overload. Though the audience has more alternatives while choosing programmes, he also has to spend more and more time to read the on-line information about the programme contents or browse different channels in order to decide what to watch. One way to overcome such a problem is to build intelligent recommender systems to provide personalized information services. By analyzing the information collected from the user, a personalized recommender system is able to reason his personal preferences and then choose the programmes for him. This paper presents a multi-agent framework in which a decision tree-based approach is proposed to learn a user’s preferences. The experimental studies concentrate on how to recommend film and news programmes to a user, and on how the system can adapt to a user’s most recent preferences. The results and analysis show the promise of our system.
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Wu, Huei-Huan, and 吳蕙圜. "Agent-based Supplier Selection System." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/51881423404600125693.

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Частини книг з теми "Multi agent system-Supplier selection"

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Griffiths, Nathan, and Michael Luck. "Cooperative Plan Selection Through Trust." In Multi-Agent System Engineering, 162–74. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-48437-x_14.

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Ounnar, Fouzia, Olivier Labarthe, Patrick Pujo, and Benoit Montreuil. "Multicriteria Supplier Selection for Supply Chain Management." In Service Orientation in Holonic and Multi-Agent Manufacturing, 27–40. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73751-5_3.

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3

Achatbi, Iman, Khalid Amechnoue, and Saloua Aoulad Allouch. "An Ontology Based Approach to Organize Supplier and Transportation Provider Selection Negotiation in Multi-agent System Model." In Lecture Notes in Networks and Systems, 129–37. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69137-4_13.

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Urbani, Dominique, and Marielle Delhom. "Water Management Policy Selection Using a Decision Support System Based on a Multi-agent System." In Lecture Notes in Computer Science, 466–69. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11558590_46.

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Bez, Marta R., Cecília D. Flores, João M. L. Fonseca, Vinicius Maroni, Paulo R. Barros, and Rosa M. Vicari. "Influence Diagram for Selection of Pedagogical Strategies in a Multi-Agent System Learning." In Lecture Notes in Computer Science, 621–30. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34654-5_63.

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Bellakhal, Raja, and Khaled Ghédira. "Learning to Negotiate Optimally in a Multi-agent Based Negotiation System for Web Service Selection." In Proceedings of SAI Intelligent Systems Conference (IntelliSys) 2016, 261–80. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56991-8_20.

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Su, Ke, and WeiZhou Song. "Based on Multi-Agent Systems (MAS) of the Prototype Selection System of Virtual Enterprise Partner." In Future Control and Automation, 323–28. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31003-4_41.

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Hernes, Marcin, Adrianna Kozierkiewicz, and Marcin Pietranik. "The Agents’ Selection Methods for a Consensus-Based Investment Strategy in a Multi-agent Financial Decisions Support System." In Communications in Computer and Information Science, 60–67. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30278-8_8.

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Silva, Vanessa B. S., and Fernando Schramm. "A Multi-criteria Decision Support System for Supplier Selection." In Decision Models in Engineering and Management, 129–41. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-11949-6_7.

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Henane, Islem, Lamjed Ben Said, Sameh Hadouaj, and Nasr Ragged. "Multi-agent Based Simulation of Animal Food Selective Behavior in a Pastoral System." In Agent and Multi-Agent Systems: Technologies and Applications, 283–92. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13480-7_30.

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Тези доповідей конференцій з теми "Multi agent system-Supplier selection"

1

Zhu, Zhongyi, Zhebin Xue, and Xianyi Zeng. "Sustainability driven apparel supplier selection." In Conference on Machine learning, Multi Agent and Cyber Physical Systems (FLINS 2022). WORLD SCIENTIFIC, 2023. http://dx.doi.org/10.1142/9789811269264_0062.

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2

Wang Yu, Jiang Ying, and Zhang Qiuyue. "An approach of supplier selection based on multi-agents system." In 2007 IEEE International Conference on Grey Systems and Intelligent Services. IEEE, 2007. http://dx.doi.org/10.1109/gsis.2007.4443526.

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3

Drakaki, Maria, Hacer Gören, and Panagiotis Tzionas. "A Multi-Agent based Decision Framework for Sustainable Supplier Selection, Order Allocation and Routing Problem." In Special Session on Logistics and Transport in the Industry 4.0. SCITEPRESS - Science and Technology Publications, 2019. http://dx.doi.org/10.5220/0007833300002179.

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4

Drakaki, Maria, Hacer Gören, and Panagiotis Tzionas. "A Multi-Agent based Decision Framework for Sustainable Supplier Selection, Order Allocation and Routing Problem." In Special Session on Logistics and Transport in the Industry 4.0. SCITEPRESS - Science and Technology Publications, 2019. http://dx.doi.org/10.5220/0007833306210628.

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5

Chen, S., K. Tai, and Z. Li. "Evaluation of supply chain resilience enhancement with multi-tier supplier selection policy using agent-based modeling." In 2016 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). IEEE, 2016. http://dx.doi.org/10.1109/ieem.2016.7797849.

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Said, Fatma Ben, and Adel M. Alimi. "Multi Agent-Learner based Online Feature Selection system." In 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE, 2016. http://dx.doi.org/10.1109/smc.2016.7844801.

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Gong, Yi, Yong Fang, Liang Liu, and Juan Li. "Multi-agent Intrusion Detection System Using Feature Selection Approach." In 2014 Tenth International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP). IEEE, 2014. http://dx.doi.org/10.1109/iih-msp.2014.137.

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Wang, Jue, Xiaobo Peng, and Derek Yip-Hoi. "A Multi-Agent System for Distributed, Internet Enabled Cutter/Workpiece Engagement Extractions." In ASME 2006 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2006. http://dx.doi.org/10.1115/detc2006-99379.

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Анотація:
Cutter/workpiece engagement (CWE) extraction is an important problem in process modeling. One approach is to use a B-rep solid modeler to perform the calculations. However, this can have a high computational overhead especially for complicated workpieces. This paper presents a multi-agent system for B-rep based CWE extraction that allows distributed processing of the modeling steps over the Internet. The CWE calculation utilizes distributed agents for performing swept volume and removal volume construction in addition to the extraction of the CWE geometry itself. These distributed agents provide the capability to perform many of the calculations in parallel. The proposed methodology thus makes the best use of available, distributed computing resources leading to greatly improved efficiency in the CWE calculations. If agents are available to perform these calculations using other non-B-rep approaches the proposed framework facilitates their integration. This paper presents the architecture of the framework. This requires a specification of each agent in the framework. The mechanisms adopted for the three primary agent actions, task scheduling, master agent selection and results passing are presented. Interaction protocols are provided to explain how agents cooperate with each other to achieve parallel computation. Finally a prototype implementation and an example are given to show the effectiveness and efficiency of the system.
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Cao, Mukun. "Multi-strategy Selection Supported Automated Negotiation System Based on BDI Agent." In 2012 45th Hawaii International Conference on System Sciences (HICSS). IEEE, 2012. http://dx.doi.org/10.1109/hicss.2012.442.

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10

Wie, Kyung-Hoon, Hyung-Jung Kim, Young-Sun Hong, and Sung-Hoon Ahn. "Agent-Based Micro Machining System With Cusp-Height-Minimized Tool Sequence." In ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/detc2009-86951.

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Анотація:
Agent technology can provide a systematic way to design and implement efficiently distributed intelligent manufacturing systems. Multi-agent system has been recognized as a promising paradigm to integrate a number of agents with different functions. In micro machining field many researchers have been studied the machining characteristics since the influence of underlying mechanisms are fundamentally different from macro-scale machining. This paper presents an agent-based micro machining system. To cover the process planning step for micro machining, basic agents such as cutting tool selection, tool-path generation, and machining cost estimation were implemented. To build and integrate these distributed agents, Java Agent Development Framework (JADE) was used. Throughout this system the selection of optimal roughing tool for semi-finishing stage was implemented by providing automated process planner for micro machining to the engineers. Machining data bases were constructed to store the information of materials, tools, and capability of available machine tools. A designed part can be uploaded to the Micro Machining (MM) agent as a Stereo Lithography (STL) format. MM agent can provide process parameters for 3-axis micro milling and tool sequence for cost-optimal machining automatically. Machining Cost Estimation agent can calculate micro machining cost for the designed part. To test the multi-agent system, a surface of micro-surface feature was fabricated with micro end-mills.
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