Title of article :
Robust forensic-based investigation algorithm for resource leveling in multiple projects
Author/Authors :
Tran ، D.-H. Faculty of Civil Engineering - Ho Chi Minh City University of Technology (HCMUT), Vietnam. - Vietnam National University Ho Chi Minh City , Le ، H.Q.-Ph. - Faculty of Civil Engineering, Vietnam. Faculty of Civil Engineering - Ho Chi Minh City University of Technology (HCMUT) - Vietnam National University Ho Chi Minh City, Can Tho University of Technology , Nguyen ، N.-Th. Faculty of Building and Industrial Construction - Hanoi University of Civil Engineering (HUCE) , Le ، Th.-T. Faculty of Civil Engineering - Ho Chi Minh City University of Technology (HCMUT)
From page :
603
To page :
618
Abstract :
The project managers often face challenging due to a scarcity of resources in construction management. Levelling the used resources in multiple projects is a frequently encountered problem in construction areas and manufacturing sectors. This study proposes a robust forensic-based investigation (FBI) algorithm for resource leveling in multiple projects with considerations of different objective functions of resource graphs. The fuzzy c-means clustering approach is fused into the main operation of the FBI to enhance the rate of convergence by utilizing population information. The scheduling examines different objective functions for optimizing resource profile selection. Two application case studies are used to demonstrate the performance of the improved optimization algorithm in dealing with the resource-leveling problem in multiple projects. Experimental findings and statistical comparisons demonstrated that the developed FFBI could acquire high quality solutions and surpass those of compared optimization algorithms.
Keywords :
Resource levelling , Fuzzy clustering , Forensic , based investigation algorithm , optimization
Journal title :
Scientia Iranica(Transactions A: Civil Engineering)
Journal title :
Scientia Iranica(Transactions A: Civil Engineering)
Record number :
2775972
Link To Document :
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