scholarly journals A Multi-agent System Model for Partner Selection Process in Virtual Enterprise

2014 ◽  
Vol 36 ◽  
pp. 367-372 ◽  
Author(s):  
B. Lotfi Sadigh ◽  
F. Arikan ◽  
A.M. Ozbayoglu ◽  
H.O. Unver ◽  
S.E. Kilic
2016 ◽  
Vol 8 (1) ◽  
pp. 46-68 ◽  
Author(s):  
George Wamamu Musumba ◽  
Patrick Kanyi Wamuyu

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.


2008 ◽  
Vol 144 ◽  
pp. 232-237
Author(s):  
Durmus Karayel ◽  
Sinan Serdar Ozkan ◽  
Fahri Vatansever

In this study, an intelligent system model that can evaluate experimental material properties and safety factors is developed. The model contains Artificial Intelligence Technologies such as Artificial Neural Network (ANN) and Fuzzy Logic. It consists of sub modules into interaction. Also, the model can obtain more precision values than interpolation techniques used to classical design. The study contributes to define safety factors, design criterions and safety stress according to a new approach based on information technologies. So, this study can be seen as one of the sub modules of Intelligence Multi Agent System and it can be integrated with Multi Agent System Model for design. Also, it can be used for classical design studies so that results can be quickly obtained. It is expected that this approach will be widely used by designers.


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