A Multi-Objective Trade-Off Model in Sustainable Construction Projects
Abstract
:1. Introduction
2. Literature Review
2.1. Objectives of Sustainable Projects
2.2. Multi-Objective Trade-off in Sustainable Construction
3. Model Description and Solution
3.1. Model Description
3.2. Model Solution
4. Model Analysis and Simulations
4.1. Model Analysis
4.2. Model Simulations
4.2.1. The Effects of the Effort Levels of the Contractor (a1, a2) on the Project Benefits (U)
4.2.2. The Effects of the Benefit Allocation Coefficient (β) on the Project Benefits (U)
4.2.3. The Effects of the Objective Relative Importance (p, q) on Effort Levels of the Contractor (a1, a2)
4.2.4. The Effects of the Objective Relative Importance (p, q) on the Benefit Allocation Coefficient (β)
4.2.5. The Effects of Effort Cost Coefficients (η1, η2) on the Benefit Allocation Coefficient (β)
4.2.6. The Effects of the Objective Relative Importance (p, q) on the Project Benefits (U)
4.2.7. The Numerical Example of the Multi-Objective Trade-off Model
5. Conclusions and Implications
Acknowledgments
Conflicts of Interest
References
- Matar, M.M.; Georgy, M.E.; Ibrahim, M.E. Sustainable construction management: Introduction of the operational context space (OCS). Constr. Manag. Econ. 2008, 26, 261–275. [Google Scholar] [CrossRef]
- Czarnecki, L.; Kaproń, M.; Van Gemert, D. Sustainable construction: Challenges, contribution of polymers, researches arena. Restor. Build. Monum. 2013, 19, 81–96. [Google Scholar] [CrossRef]
- Robins, F. The challenge of TBL: A responsibility to whom? Bus. Soc. Rev. 2006, 111, 1–14. [Google Scholar] [CrossRef]
- Czarnecki, L.; Kaproń, M. Sustainable construction as a research area. Int. J. Soc. Mater. Eng. Resour. 2010, 17, 99–106. [Google Scholar] [CrossRef]
- Schröpfer, V.L.M.; Tah, J.; Kurul, E. Mapping the knowledge flow in sustainable construction project teams using social network analysis. Eng. Constr. Archit. Manag. 2017, 24, 229–259. [Google Scholar] [CrossRef]
- Glass, J. The state of sustainability reporting in the construction sector. Smart Sustain. Built Environ. 2012, 1, 87–104. [Google Scholar] [CrossRef]
- Karakhan, A.A.; Gambatese, J.A. Identification, quantification, and classification of potential safety risk for sustainable construction in the United States. J. Constr. Eng. Manag. 2017, 143, 1–10. [Google Scholar] [CrossRef]
- Manoliadis, O.; Tsolas, I.; Nakou, A. Sustainable construction and drivers of change in Greece: A Delphi study. Constr. Manag. Econ. 2006, 24, 113–120. [Google Scholar] [CrossRef]
- Sfakianaki, E. Resource-efficient construction: Rethinking construction towards sustainability. World J. Sci. Technol. Sustain. Dev. 2015, 12, 233–242. [Google Scholar] [CrossRef]
- Shi, L.; Ye, K.; Lu, W.; Hu, X. Improving the competence of construction management consultants to underpin sustainable construction in China. Habitat Int. 2014, 41, 236–242. [Google Scholar] [CrossRef] [Green Version]
- Li, H.; Zhang, X.; Ng, S.T.; Skitmore, M. Quantifying stakeholder influence in decision/evaluations relating to sustainable construction in China—A Delphi approach. J. Clean. Prod. 2017, 1–11. [Google Scholar] [CrossRef]
- Whang, S.W.; Kim, S. Balanced sustainable implementation in the construction industry: The perspective of Korean contractors. Energy Build. 2015, 96, 76–85. [Google Scholar] [CrossRef]
- Karakhan, A.A. LEED-certified projects: Green or sustainable? J. Manag. Eng. 2016, 32, 1–3. [Google Scholar] [CrossRef]
- Gan, X.; Zuo, J.; Ye, K.; Skitmore, M.; Xiong, B. Why sustainable construction? Why not? An owner’s perspective. Habitat Int. 2015, 47, 61–68. [Google Scholar] [CrossRef]
- Tan, Y.; Shen, L.; Yao, H. Sustainable construction practice and contractors’ competitiveness: A preliminary study. Habitat Int. 2011, 35, 225–230. [Google Scholar] [CrossRef]
- Xue, X.; Shen, Q.; Ren, Z. Critical review of collaborative working in construction projects: Business environment and human behaviors. J. Manag. Eng. 2010, 26, 196–208. [Google Scholar] [CrossRef]
- Wu, G.; Zuo, J.; Zhao, X. Incentive model based on cooperative relationship in sustainable construction projects. Sustainability 2017, 9, 1191. [Google Scholar] [CrossRef]
- Schieg, M. Strategies for avoiding asymmetric information in construction project management. J. Bus. Econ. Manag. 2008, 9, 47–51. [Google Scholar] [CrossRef]
- Dai, R.; Zhang, J.; Tang, W. Cartelization or cost-sharing? Comparison of cooperation modes in a green supply chain. J. Clean. Prod. 2017, 156, 159–173. [Google Scholar] [CrossRef]
- Menesi, W.; Golzarpoor, B.; Hegazy, T. Fast and near-optimum schedule optimization for large-scale projects. J. Constr. Eng. Manag. 2013, 139, 1117–1124. [Google Scholar] [CrossRef]
- Chakraborty, S.; Jo, B.W.; Jo, J.H.; Baloch, Z. Effectiveness of sewage sludge ash combined with waste pozzolanic minerals in developing sustainable construction material: An alternative approach for waste management. J. Clean. Prod. 2017, 153, 253–263. [Google Scholar] [CrossRef]
- Kerkhove, L.P.; Vanhoucke, M. Incentive contract design for projects: The owner’s perspective. Omega 2016, 62, 93–114. [Google Scholar] [CrossRef]
- Zhong, Y.; Wu, P. Economic sustainability, environmental sustainability and constructability indicators related to concrete- and steel-projects. J. Clean. Prod. 2015, 108, 748–756. [Google Scholar] [CrossRef]
- Jafari, H.; Hejazi, S.R.; Rasti-Barzoki, M. Sustainable development by waste recycling under a three-echelon supply chain: A game-theoretic approach. J. Clean. Prod. 2017, 142, 2252–2261. [Google Scholar] [CrossRef]
- Kerkhove, L.P.; Vanhoucke, M. A parallel multi-objective scatter search for optimising incentive contract design in projects. Eur. J. Oper. Res. 2017, 261, 1066–1084. [Google Scholar] [CrossRef]
- Myerson, R. Game theory: Analysis of Conflict; Harvard University: Cambridge, MA, USA, 1991. [Google Scholar]
- San Cristobal, J. The use of Game Theory to solve conflicts in the project management and construction industry. Int. J. Inf. Syst. Proj. Manag. 2015, 3, 43–58. [Google Scholar]
- Huang, X.; He, P.; Zhang, W. A cooperative differential game of transboundary industrial pollution between two regions. J. Clean. Prod. 2016, 120, 43–52. [Google Scholar] [CrossRef]
- Chen, T.C.; Lin, Y.C.; Wang, L.C. The analysis of BOT strategies based on game theory—Case study on Taiwan’s high speed railway project. J. Civ. Eng. Manag. 2012, 18, 662–674. [Google Scholar] [CrossRef]
- He, W.; Tang, W.; Wei, Y.; Duffield, C.F.; Lei, Z. Evaluation of cooperation during project delivery: Empirical study on the hydropower industry in southwest China. J. Constr. Eng. Manag. 2016, 142, 1–10. [Google Scholar] [CrossRef]
- Javed, A.A.; Lam, P.T.I.; Chan, A.P.C. Change negotiation in public-private partnership projects through output specifications: An experimental approach based on game theory. Constr. Manag. Econ. 2014, 32, 323–348. [Google Scholar] [CrossRef]
- Chong, W.K.; Kumar, S.; Haas, C.T.; Beheiry, S.M.; Coplen, L.; Oey, M. Understanding and interpreting baseline perceptions of sustainability in construction among civil engineers in the United States. J. Manag. Eng. 2009, 25, 143–154. [Google Scholar] [CrossRef]
- Shen, L.; Tam, V.W.Y.; Tam, L.; Ji, Y. Project feasibility study: The key to successful implementation of sustainable and socially responsible construction management practice. J. Clean. Prod. 2010, 18, 254–259. [Google Scholar] [CrossRef]
- Ahn, C.; Lee, S.H.; Peña-Mora, F.; Abourizk, S. Toward environmentally sustainable construction processes: The U.S. and Canada’s perspective on energy consumption and GHG/CAP emissions. Sustainability 2010, 2, 354–370. [Google Scholar] [CrossRef]
- Zimmermann, M.; Althaus, H.J.; Haas, A. Benchmarks for sustainable construction: A contribution to develop a standard. Energy Build. 2005, 37, 1147–1157. [Google Scholar] [CrossRef]
- Huang, R.; Yeh, C. Development of an assessment framework for green highway construction. J. Chin. Inst. Eng. 2008, 31, 573–585. [Google Scholar] [CrossRef]
- Bassioni, H.A.; Price, A.D.F.; Hassan, T.M. Building a conceptual framework for measuring business performance in construction: An empirical evaluation. Constr. Manag. Econ. 2005, 23, 495–507. [Google Scholar] [CrossRef]
- Chen, Y.; Okudan, G.E.; Riley, D.R. Sustainable performance criteria for construction method selection in concrete buildings. Autom. Constr. 2010, 19, 235–244. [Google Scholar] [CrossRef]
- Ding, G.K.C. Sustainable construction-The role of environmental assessment tools. J. Environ. Manag. 2008, 86, 451–464. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Shen, L.; Tam, V.W.Y.; Li, C. Benefit analysis on replacing in situ concreting with precast slabs for temporary construction works in pursuing sustainable construction practice. Resour. Conserv. Recycl. 2009, 53, 145–148. [Google Scholar] [CrossRef]
- Presley, A.; Meade, L. Benchmarking for sustainability: An application to the sustainable construction industry. Benchmarking An Int. J. 2010, 17, 435–451. [Google Scholar] [CrossRef]
- Huang, R.Y.; Hsu, W.T. Framework development for state-level appraisal indicators of sustainable construction. Civ. Eng. Environ. Syst. 2011, 28, 143–164. [Google Scholar] [CrossRef]
- Fortunato, B.R.; Hallowell, M.R.; Behm, M.; Dewlaney, K. Identification of safety risks for high-performance sustainable construction projects. J. Constr. Eng. Manag. 2012, 138, 499–508. [Google Scholar] [CrossRef]
- Kibwami, N.; Tutesigensi, A. Enhancing sustainable construction in the building sector in Uganda. Habitat Int. 2016, 57, 64–73. [Google Scholar] [CrossRef]
- Marjaba, G.E.; Chidiac, S.E. Sustainability and resiliency metrics for buildings—Critical review. Build. Environ. 2016, 101, 116–125. [Google Scholar] [CrossRef]
- Ozcan-Deniz, G.; Zhu, Y. A multi-objective decision-support model for selecting environmentally conscious highway construction methods. J. Civ. Eng. Manag. 2015, 21, 733–747. [Google Scholar] [CrossRef]
- He, K.; Tang, R.; Jin, M. Pareto fronts of machining parameters for trade-off among energy consumption, cutting force and processing time. Int. J. Prod. Econ. 2017, 185, 113–127. [Google Scholar] [CrossRef]
- Brucker, P.; Drexl, A.; Möhring, R.; Neumann, K.; Pesch, E. Resource-constrained project scheduling: Notation, classification, models, and methods. Eur. J. Oper. Res. 1999, 112, 3–41. [Google Scholar] [CrossRef]
- Heilmann, R. A branch-and-bound procedure for the multi-mode resource-constrained project scheduling problem with minimum and maximum time lags. Eur. J. Oper. Res. 2003, 144, 348–365. [Google Scholar] [CrossRef]
- Xu, N.; McKee, S.A.; Nozick, L.K.; Ufomata, R. Augmenting priority rule heuristics with justification and rollout to solve the resource-constrained project scheduling problem. Comput. Oper. Res. 2008, 35, 3284–3297. [Google Scholar] [CrossRef]
- Agarwal, A.; Colak, S.; Erenguc, S. A Neurogenetic approach for the resource-constrained project scheduling problem. Comput. Oper. Res. 2011, 38, 44–50. [Google Scholar] [CrossRef]
- Chen, R.M. Particle swarm optimization with justification and designed mechanisms for resource-constrained project scheduling problem. Expert Syst. Appl. 2011, 38, 7102–7111. [Google Scholar] [CrossRef]
- Dave, B.; Koskela, L. Collaborative knowledge management—A construction case study. Autom. Constr. 2009, 18, 894–902. [Google Scholar] [CrossRef]
- Hanna, A.S.; Thomas, G.; Swanson, J.R. Construction risk identification and allocation: Cooperative approach. J. Constr. Eng. Manag. 2013, 139, 1098–1107. [Google Scholar] [CrossRef]
- Khanzadi, M.; Eshtehardian, E.; Chalekaee, A. A game theory approach for optimum strategy of the owner and contractor in delayed projects. J. Civ. Eng. Manag. 2016, 22, 1066–1077. [Google Scholar] [CrossRef]
- Wang, Y.; Liu, J. Evaluation of the excess revenue sharing ratio in PPP projects using principal-agent models. Int. J. Proj. Manag. 2015, 33, 1317–1324. [Google Scholar] [CrossRef]
- Weeusen, W.; van Den Broeck, J. Efficiency estimation from Cobb-Douglas production functions with composed error. Int. Econ. Rev. 1997, 18, 435–444. [Google Scholar]
- Von der Osten, F.B.; Kirley, M.; Miller, T. Sustainability is possible despite greed—Exploring the nexus between profitability and sustainability in common pool resource systems. Sci. Rep. 2017, 7, 2307. [Google Scholar] [CrossRef] [PubMed]
- Wu, G.D. Project-based supply chain cooperative incentive based on reciprocity preference. Int. J. Simul. Model. 2014, 13, 102–115. [Google Scholar] [CrossRef]
- Fu, Y.; Chen, Y.; Zhang, S.; Wang, W. Promoting cooperation in construction projects: An integrated approach of contractual incentive and trust. Constr. Manag. Econ. 2015, 33, 653–670. [Google Scholar] [CrossRef]
- Shi, J.; Wu, G.; Tang, D. Project-based supply chain cross-organizational incentives based on duration-quality coordinative equilibrium. J. Ind. Eng. Eng. Manag. 2012, 26, 58–64. [Google Scholar]
- Wu, G.D. Knowledge collaborative incentive based on inter-organizational cooperative innovation of project-based supply chain. J. Ind. Eng. Manag. 2013, 6, 1065–1081. [Google Scholar] [CrossRef]
- Hosseinian, S.M.; Carmichael, D.G. Optimal gainshare/painshare in alliance projects. J. Oper. Res. Soc. 2013, 64, 1269–1278. [Google Scholar] [CrossRef]
- Wu, G.D.; Tang, D.Z. Inter-organizational cooperative innovation of project-based supply chains under consideration of monitoring signals. Int. J. Simul. Model. 2015, 14, 539–550. [Google Scholar] [CrossRef]
- Wang, Y.; Ma, X.; Li, Z.; Liu, Y.; Xu, M.; Wang, Y. Profit distribution in collaborative multiple centers vehicle routing problem. J. Clean. Prod. 2017, 144, 203–219. [Google Scholar] [CrossRef]
(a1, a2) | β | U1 | U2 | U | ||
---|---|---|---|---|---|---|
η1 = 2, η2 = 2 | p = 0.5, q = 0.5 | (1.25, 1.25) | 0.5 | 2.06 | 2.06 | 4.12 |
p = 0.7, q = 0.3 | (1.60, 1.05) | 0.52 | 2.72 | 2.51 | 5.23 | |
p = 0.9, q = 0.1 | (2.38, 0.79) | 0.59 | 2.63 | 1.84 | 4.47 | |
η1 = 2, η2 = 4 | p = 0.5, q = 0.5 | (2.10, 1.49) | 0.41 | 3.62 | 5.21 | 8.83 |
p = 0.7, q = 0.3 | (2.78, 1.29) | 0.46 | 5.07 | 5.95 | 11.02 | |
p = 0.9, q = 0.1 | (3.89, 0.92) | 0.57 | 6.18 | 4.66 | 10.84 | |
η1 = 4, η2 = 2 | p = 0.5, q = 0.5 | (1.49, 2.10) | 0.41 | 3.62 | 5.21 | 8.83 |
p = 0.7, q = 0.3 | (1.71, 1.48) | 0.40 | 3.34 | 5.01 | 8.35 | |
p = 0.9, q = 0.1 | (2.09, 0.98) | 0.43 | 4.16 | 5.51 | 9.67 | |
η1 = 2, η2 = 8 | p = 0.5, q = 0.5 | (1.77, 0.88) | 0.33 | 2.06 | 4.18 | 6.24 |
p = 0.7, q = 0.3 | (2.50, 0.82) | 0.42 | 3.75 | 5.19 | 8.94 | |
p = 0.9, q = 0.1 | (3.76, 0.63) | 0.55 | 4.25 | 3.47 | 7.72 | |
η1 = 8, η2 = 2 | p = 0.5, q = 0.5 | (0.88, 1.77) | 0.33 | 2.06 | 4.18 | 6.24 |
p = 0.7, q = 0.3 | (0.95, 1.24) | 0.29 | 1.49 | 3.65 | 5.14 | |
p = 0.9, q = 0.1 | (1.08, 0.72) | 0.30 | 1.56 | 3.63 | 5.19 |
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Wu, G. A Multi-Objective Trade-Off Model in Sustainable Construction Projects. Sustainability 2017, 9, 1929. https://doi.org/10.3390/su9111929
Wu G. A Multi-Objective Trade-Off Model in Sustainable Construction Projects. Sustainability. 2017; 9(11):1929. https://doi.org/10.3390/su9111929
Chicago/Turabian StyleWu, Guangdong. 2017. "A Multi-Objective Trade-Off Model in Sustainable Construction Projects" Sustainability 9, no. 11: 1929. https://doi.org/10.3390/su9111929