Using Intelligent Techniques in Construction Project Cost Estimation: 10-Year Survey

Cost estimation is the most important preliminary process in any construction project. Therefore, construction cost estimation has the lion’s share of the research effort in construction management. In this paper, we have analysed and studied proposals for construction cost estimation for the last 10 years. To implement this survey, we have proposed and applied a methodology that consists of two parts. The first part concerns data collection, for which we have chosen special journals as sources for the surveyed proposals. The second part concerns the analysis of the proposals. To analyse each proposal, the following four questions have been set. Which intelligent technique is used? How have data been collected? How are the results validated? And which construction cost estimation factors have been used? From the results of this survey, two main contributions have been produced. The first contribution is the defining of the research gap in this area, which has not been fully covered by previous proposals of construction cost estimation. The second contribution of this survey is the proposal and highlighting of future directions for forthcoming proposals, aimed ultimately at finding the optimal construction cost estimation. Moreover, we consider the second part of our methodology as one of our contributions in this paper. This methodology has been proposed as a standard benchmark for construction cost estimation proposals.

[1]  Dominic D. Ahiaga-Dagbui,et al.  Rethinking Construction Cost Overruns: Cognition, Learning and Estimation , 2014 .

[2]  Richard L. Tucker,et al.  Impacts of Design/Information Technology on Project Outcomes , 2004 .

[3]  Jung-Ho Yu,et al.  BIM and ontology-based approach for building cost estimation , 2014 .

[4]  Irem Dikmen,et al.  Multiagent System to Simulate Risk-Allocation and Cost-Sharing Processes in Construction Projects , 2013, J. Comput. Civ. Eng..

[5]  Martin Skitmore,et al.  The effect of client and type and size of construction work on a contractor's bidding strategy , 2001 .

[6]  Changmin Kim,et al.  Hybrid principal component analysis and support vector machine model for predicting the cost performance of commercial building projects using pre-project planning variables , 2012 .

[7]  Krzysztof Schabowicz,et al.  Estimation of earthworks execution time cost by means of artificial neural networks , 2010 .

[8]  Moonseo Park,et al.  Case Adaptation Method of Case-Based Reasoning for Construction Cost Estimation in Korea , 2012 .

[9]  Simon Smith,et al.  Neural networks for modelling the final target cost of water projects , 2012 .

[10]  Kyoungmin Kim,et al.  Preliminary Cost Estimation Model Using Case-Based Reasoning and Genetic Algorithms , 2010, J. Comput. Civ. Eng..

[11]  Eddy M. Rojas,et al.  Multi-Agent Framework for General-Purpose Situational Simulations in the Construction Management Domain , 2006 .

[12]  Hyung Jin Kim,et al.  A hybrid conceptual cost estimating model for large building projects , 2012 .

[13]  Min-Yuan Cheng,et al.  Hybrid intelligence approach based on LS-SVM and Differential Evolution for construction cost index estimation: A Taiwan case study , 2013 .

[14]  Ehsan Eshtehardian,et al.  Multi-mode resource-constrained discrete time–cost-resource optimization in project scheduling using non-dominated sorting genetic algorithm , 2013 .

[15]  Hun Hee Cho,et al.  Application of support vector machines in assessing conceptual cost estimates , 2007 .

[16]  Irem Dikmen,et al.  A knowledge-based risk mapping tool for cost estimation of international construction projects , 2014 .

[17]  Ibrahim Mahamid,et al.  Early cost estimating for road construction projects using multiple regression techniques , 2011 .

[18]  Chester G. Wilmot,et al.  Neural Network Modeling of Highway Construction Costs , 2005 .

[19]  Ali Kaveh,et al.  Nondominated Archiving Multicolony Ant Algorithm in Time-Cost Trade-Off Optimization , 2009 .

[20]  Andrew D.F. Price,et al.  Relationship between value and duration for construction projects , 1991 .

[21]  James M. Neil Construction Cost Estimating for Project Control , 1981 .

[22]  Garold D. Oberlender,et al.  Predicting accuracy of early cost estimates based on estimate quality , 2001 .

[23]  Miroslaw J. Skibniewski,et al.  Integrating Neurofuzzy System with Conceptual Cost Estimation to Discover Cost-Related Knowledge from Residential Construction Projects , 2010, J. Comput. Civ. Eng..

[24]  G. Edward Gibson,et al.  Building Project Scope Definition Using Project Definition Rating Index , 2001 .

[25]  Kyung In Kang,et al.  Hybrid Models of Neural Networks and Genetic Algorithms for Predicting Preliminary Cost Estimates , 2005 .

[26]  Suzanne Wilkinson,et al.  Application of Artificial Neural Network Methodology for Predicting Seismic Retrofit Construction Costs , 2014 .

[27]  Chimay J. Anumba,et al.  A System of Systems Approach to Intelligent Construction Systems , 2009 .

[28]  B. Akinci,et al.  FACTORS AFFECTING CONTRACTORS' RISK OF COST OVERBURDEN , 1998 .

[29]  Sheryl Staub-French,et al.  A generic feature-driven activity-based cost estimation process , 2003, Adv. Eng. Informatics.

[30]  S. Thomas Ng,et al.  An ant colony system based decision support system for construction time-cost optimization , 2012 .

[31]  Wojciech Bożejko,et al.  Time/cost optimization using hybrid evolutionary algorithm in construction project scheduling , 2008 .

[32]  Mounir Khalil El Debs,et al.  A cost optimization-based design of precast concrete floors using genetic algorithms , 2012 .

[33]  Ian C. Parmee Computational Intelligence and Civil Engineering—Perceived Problems and Possible Solutions , 2003 .

[34]  Sangyong Kim,et al.  Hybrid forecasting system based on case-based reasoning and analytic hierarchy process for cost estimation , 2013 .

[35]  Keith R. Molenaar,et al.  Construction Project Cost Escalation Factors , 2009 .

[36]  Ian Flood,et al.  Neural Networks in Civil Engineering. I: Principles and Understanding , 1994 .

[37]  Seung Heon Han,et al.  Conceptual Cost-Prediction Model for Public Road Planning via Rough Set Theory and Case-Based Reasoning , 2014 .

[38]  Min-Yuan Cheng,et al.  Interval estimation of construction cost at completion using least squares support vector machine , 2014 .

[39]  Kleopatra Petroutsatou,et al.  Early Cost Estimating of Road Tunnel Construction Using Neural Networks , 2012 .

[40]  Hani G. Melhem,et al.  Technical Council for Computing and Information Technology , 2008 .

[41]  Jie Gong,et al.  Predicting construction cost overruns using text mining, numerical data and ensemble classifiers , 2014 .

[42]  Will Hughes,et al.  The influence of project complexity on estimating accuracy , 2000 .

[43]  Hong Zhang,et al.  Fuzzy-multi-objective particle swarm optimization for time―cost―quality tradeoff in construction , 2010 .

[44]  Roger Flanagan,et al.  THE IMPACT OF EFFECTIVE MATERIAL MANAGEMENT ON CONSTRUCTION SITE PERFORMANCE FOR SMALL AND MEDIUM SIZED CONSTRUCTION ENTERPRISES , 2009 .

[45]  S. W. Nunnally Construction methods and management , 1980 .

[46]  Min-Yuan Cheng,et al.  Web-based conceptual cost estimates for construction projects using Evolutionary Fuzzy Neural Inference Model , 2009 .