Please use this identifier to cite or link to this item: http://elar.urfu.ru/handle/10995/75636
Title: Hybrid Agents Implementation for the Control of the Construction Company
Authors: Aksyonov, K.
Bykov, E.
Aksyonova, O.
Nevolina, A.
Goncharova, N.
Issue Date: 2017
Publisher: Elsevier B.V.
Citation: Hybrid Agents Implementation for the Control of the Construction Company / K. Aksyonov, E. Bykov, O. Aksyonova et al. // Procedia Computer Science. — 2017. — Vol. 105. — P. 215-220.
Abstract: Planning the project duration together with separate works is an essential element of managing the construction. The final duration depends on multiple factors, including the funds, customer requests, and capabilities of the construction company. In order to avoid additional costs in penalties or additional expenses, the management needs to estimate the real construction duration in advance, before the contract is signed. Further on, these terms need to be monitored both in whole and for the specific jobs in order to be able to edit further stages with regard of the remaining time, resources and used resources ratio. The development of a decision support system for the construction company is a pressing problem due to the growing demand in decision making persons' labor automation in planning and monitoring the construction processes. The paper presents the model and the application experience for such a system. © 2017 The Authors.
Keywords: CONSTRUCTION
CONTROL
DECISION SUPPORT
MULTI-AGENT SIMULATION
PLANNING
SUBCONTRACT
ARTIFICIAL INTELLIGENCE
CONSTRUCTION
CONSTRUCTION INDUSTRY
CONTROL
DECISION MAKING
INTELLIGENT CONTROL
MULTI AGENT SYSTEMS
PLANNING
ROBOTICS
SMART SENSORS
APPLICATION EXPERIENCES
CONSTRUCTION COMPANIES
CONSTRUCTION DURATION
DECISION MAKING PERSONS
DECISION SUPPORTS
MULTI AGENT SIMULATION
PLANNING AND MONITORING
SUBCONTRACT
DECISION SUPPORT SYSTEMS
URI: http://elar.urfu.ru/handle/10995/75636
Access: info:eu-repo/semantics/openAccess
cc-by-nc-nd
gold
Conference name: IEEE International Symposium on Robotics and Intelligent Sensors, IRIS 2016
Conference date: 17 December 2016 through 20 December 2016
SCOPUS ID: 85016095509
WOS ID: 000398830900035
PURE ID: 1687883
ISSN: 1877-0509
DOI: 10.1016/j.procs.2017.01.213
Appears in Collections:Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC

Files in This Item:
File Description SizeFormat 
2-s2.0-85016095509.pdf322,02 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.