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AuthorMukilan, K.
AuthorRameshbabu, C.
AuthorBaranitharan, B.
AuthorMuthusamy, Suresh
AuthorRamamoorthi, Ponarun
AuthorSadasivuni, Kishor Kumar
AuthorOflaz, Kamil
AuthorKhan, Anish
Available date2025-02-16T05:44:29Z
Publication Date2024
Publication NameNeural Computing and Applications
ResourceScopus
Identifierhttp://dx.doi.org/10.1007/s00521-024-10414-9
ISSN9410643
URIhttp://hdl.handle.net/10576/63052
AbstractThe Engineering Procurement Construction (EPC) contract systems are widely employed in the construction industry. Among the prevalent issues in this sector, cash flow problems frequently lead to decreased productivity and efficiency. To address these challenges, a claim management system is developed based on the Improved Monarch Butterfly Optimization Algorithm (IMBOA) and the principles of EPC. Conventional construction models typically optimize only a single objective, such as time, cost, or delay, which may not effectively enhance overall performance. This study aims to develop a claim management system based on IMBOA and EPC principles to optimize multiple objectives, focusing on minimizing project costs and time delays while ensuring high-quality results. The basic methodology of this research involves integrating EPC and claim management principles with the IMBOA algorithm to create an efficient, high-quality system. This process starts with a comprehensive literature review on EPC, claims, MBOA, and related algorithms. Common disputes and claims in the construction industry are examined, and critical factors influencing these claims are identified. The Monarch Butterfly Optimization Algorithm (MBOA) and its improved version (IMBOA) are explored for their application in optimizing project performance. A case study in China's coal mining industry evaluates the effectiveness of the EPC approach, demonstrating that it minimizes time delays and costs. The IMBOA approach proposed in this study has the potential to mitigate 23% of risks and avoid 32% of risks associated with the action plan of China's coal mining industry. Furthermore, comparative analysis with other optimization models indicates that the developed IMBOA model yields superior results, reducing overall project time by 15% and cost by 18%.
SponsorThis work was supported by the Qatar National Research Fund under grant no. MME03-1226-210042. The statements made herein are solely the responsibility of the authors.
Languageen
PublisherSpringer Science and Business Media Deutschland GmbH
SubjectClaim management system
Cost
EPC
Improved monarch butterfly optimization
Quality
Risk analysis
TitleAn efficient claim management assurance system using EPC contract based on improved monarch butterfly optimization models
TypeArticle
dc.accessType Open Access


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