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Development of Multi-Objective Scheduling Model for Construction Projects Using Opposition-Based NSGA III

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Abstract

With the aim of successfully completing the construction projects, several multi-objective scheduling models (MOSMs) have been systematically developed so far. In order to alleviate the limitations of existing MOSMs, in this paper, a multi-objective scheduling model is developed as an opposition-based non-dominated sorting genetic algorithm III (OBNSGA III). The developed model employs opposition-based learning technique in NSGA III that uses opposition numbers to generate the well diverse initial population and for generation jum**. The working efficiency of developed model is demonstrated through solving a time–cost-resources-quality trade-off optimization problem of a case study project that provides a set of Pareto-optimal solutions. The paper considers that each activity has several execution modes, which are accompanied by different amount of time, cost, resources and impact on entire project quality. Based on the performance metrics, hypothesis testing and results of developed model, the comparison between developed model and those reported in literature demonstrates the usefulness of developed model in simultaneous optimization of four objectives. Besides, outcomes of the proposed model, a value path plot to visualize more than three objectives, and a priori approach to select one solution from obtained Pareto-optimal solutions makes this paper useful to researchers and construction managers.

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Data availability statement

Some or all data, models or code that support the findings of this study are available from the corresponding author upon reasonable request.

References

  1. A.J.G. Babu, N. Suresh, Project management with time, cost, and quality considerations. Eur. J. Oper. Res. 88(2), 320–327 (1996)

    Article  Google Scholar 

  2. M.Y. Cheng, D.H. Tran, Opposition-based multiple-objective differential evolution to solve the time-cost-environment impact trade-off problem in contruction projects. J. Constr. Eng. Manag. 29(5), 04001474 (2014)

    Google Scholar 

  3. I. Das, J.E. Dennis, Normal-boundary intersection: a new method for generating the Pareto surface in nonlinear multicriteria optimization problems. SIAM J. Optim. 8(3), 631–657 (1998)

    Article  MathSciNet  Google Scholar 

  4. K. Deb, R.B. Agrawal, Simulated binary crossover for continuous search space. Complex Syst. 9(2), 115–148 (1994)

    MathSciNet  MATH  Google Scholar 

  5. K. Deb, M. Goyal, A combined genetic adaptive search (GeneAS) for engineering design. Comput. Sci. Inform. 26(4), 30–45 (1996)

    Google Scholar 

  6. K. Deb, H. Jain, An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, part I: solving problems with box constraints. IEEE Trans. Evol. Comput. 18(4), 577–601 (2014)

    Article  Google Scholar 

  7. K. El-Rayes, A. Kandil, Time-cost-quality trade-off analysis for highway construction. J. Constr. Eng. Manag. 131(4), 477–486 (2005)

    Article  Google Scholar 

  8. E. Elbeltagi, M. Ammar, H. Sanad, M. Kassab, Overall multiobjective optimization of construction projects scheduling using particle swarm. Eng. Constr. Archit. Manag. 23(3), 265–282 (2016)

    Article  Google Scholar 

  9. S.E. Elmaghraby, Activity Networks: Project Planning and Control by Network Models (Wiley, New York, 1977).

    MATH  Google Scholar 

  10. E. Fallah-Mehdipour, O. Bozorg Haddad, M.M. Rezapour Tabari, M.A. Marino, Extraction of decision alternatives in construction management projects: application and adaptation of NSGA-II and MOPSO. Expert Syst. Appl. 39(3), 2794–2803 (2012)

    Article  Google Scholar 

  11. C.-W. Feng, L. Liu, S.A. Burns, Using genetic algorithms to solve construction time-cost trade-off problems. J. Comput. Civ. Eng. 11(3), 184–189 (1997)

    Article  Google Scholar 

  12. J.C. Ferreira, C.M. Fonseca, A. Gaspar-Cunha, Methodology to select solutions from the pareto-optimal set: a comparative study, in Proceedings of GECCO 2007: Genetic and Evolutionary Computation Conference (2007), pp. 789–796

  13. F. Fu, T. Zhang, A new model for solving time-cost-quality trade-off problems in construction. PLoS ONE 11(12), e0167142 (2016)

    Article  Google Scholar 

  14. A.M. Geoffrion, J.S. Dyer, A. Feinberg, Interactive approach for multi-criterion optimization, with an application to the operation of an academic department. Manag. Sci. 19(4), 357–368 (1972)

    Article  Google Scholar 

  15. P. Ghoddousi, E. Eshtehardian, S. Jooybanpour, A. Javanmardi, Multi-mode resource-constrained discrete time-cost-resource optimization in project scheduling using non-dominated sorting genetic algorithm. Autom. Constr. 30, 216–227 (2013)

    Article  Google Scholar 

  16. F. Habibi, F. Barzinpour, S.J. Sadjadi, A multi-objective optimization model for project scheduling with time-varying resource requirements and capacities. J. Ind. Syst. Eng. 10(November), 92–118 (2017)

    Google Scholar 

  17. F. Habibi, F. Barzinpour, S.J. Sadjadi, Resource-constrained project scheduling problem: review of past and recent developments. J. Proj. Manag. 3, 55–88 (2018)

    Google Scholar 

  18. Hegazy, T. (2002) Computer-Based Construction Project Management, CIV E 596—CONSTRUCTION MANAGEMENT. https://doi.org/10.1016/B978-0-12-408090-4.00008-6

  19. E. Kalhor, M. Khanzadi, E. Eshtehardian, A. Afshar, Stochastic time-cost optimization using non-dominated archiving ant colony approach. Autom. Constr. 20(8), 1193–1203 (2011)

    Article  Google Scholar 

  20. J.E. Kelley, M.R. Walker, Critical-path planning and scheduling, in Proceedings of the Eastern Joint Computer Conference, E-AIEE-ACM 1959 (1959), pp. 160–173

  21. K. Khalili-Damghani, M. Tavana, A.-R. Abtahi, F.J. Santos Arteaga, Solving multi-mode time-cost-quality trade-off problems under generalized precedence relations. Optim. Methods Softw. 30(5), 965–1001 (2015)

    Article  MathSciNet  Google Scholar 

  22. D.B. Khang, Y.M. Myint, Time, cost and quality trade-off in project management: A case study. Int. J. Project Manage. 17(4), 249–256 (1999)

    Article  Google Scholar 

  23. M. Köppen, K. Yoshida, Many-objective particle swarm optimization by gradual leader selection, in Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Springer, Berlin, 2007), pp. 323–331

  24. S.S Leu, C.H. Yang, A genetic-algorithm-based resource-constrained construction scheduling system. Constr. Manage. Econ. 17(6), 767–776 (1999)

    Article  Google Scholar 

  25. D. Liu, H. Li, H. Wang, C. Qi, T. Rose, Discrete symbiotic organisms search method for solving large-scale time-cost trade-off problem in construction scheduling. Expert Syst. Appl. (2020). https://doi.org/10.1016/j.eswa.2020.113230

    Article  Google Scholar 

  26. D.-L. Luong, D.-H. Tran, P.T. Nguyen, Optimizing multi-mode time-cost-quality trade-off of construction project using opposition multiple objective difference evolution. Int. J. Constr. Manag. 21(3), 1–13 (2018)

    Google Scholar 

  27. W. Ma, Y. Che, H. Ke, Preemptive multi-mode resource-constrained discrete time-cost-resource optimization via non-dominated sorting genetic algorithm, in Proceedings of the 6th International Asia Conference on Industrial Engineering and Management Innovation (Atlantis Press, Paris, 2016), pp. 719–728

  28. S. Mungle et al., A fuzzy clustering-based genetic algorithm approach for time-cost-quality trade-off problems: A case study of highway construction project. Eng. Appl. Artif. Intell. 26(8), 1953–1966 (2013)

    Article  Google Scholar 

  29. A. Panwar, K.N. Jha, A many-objective optimization model for construction scheduling. Constr. Manag. Econ. 37(12), 727–739 (2019)

    Article  Google Scholar 

  30. A. Panwar, K.K. Tripathi, K.N. Jha, A qualitative framework for selection of optimization algorithm for multi-objective trade-off problem in construction projects. Eng. Constr. Archit. Manag. 26(9), 1924–1945 (2019)

    Article  Google Scholar 

  31. S. Rahnamayan, H.R. Tizhoosh, M.M.A. Salama, Opposition-based differential evolution. IEEE Trans. Evol. Comput. 12(1), 64–79 (2008)

    Article  Google Scholar 

  32. A.B. Senouci, N.N. Eldin, Use of genetic algorithms in resource scheduling of construction projects. J. Constr. Eng. Manag. 130(6), 869–877 (2004)

    Article  Google Scholar 

  33. M. Shahriari, Multi-objective optimization of discrete time–cost tradeoff problem in project networks using non-dominated sorting genetic algorithm. J. Ind. Eng. Int. 12, 159–169 (2016)

    Article  Google Scholar 

  34. K. Sharma, M.K. Trivedi, Latin hypercube sampling-based NSGA-III optimization model for multimode resource constrained time–cost–quality–safety trade-off in construction projects. Int. J. Constr. Manag. (2020). https://doi.org/10.1080/15623599.2020.1843769

    Article  Google Scholar 

  35. G. Singh, A.T. Ernst, Resource constraint scheduling with a fractional shared resource. Oper. Res. Lett. 39(5), 363–368 (2011)

    MathSciNet  MATH  Google Scholar 

  36. R.M. Storn, K. Price, Differential evolution-A simple and efficient heuristic for global optimization over continuous space. J. Glob. Optim. 11(4), 341–359 (1997)

    Article  MathSciNet  Google Scholar 

  37. S. Tiwari, S. Johari, Project scheduling by integration of time cost trade-off and constrained resource scheduling. J. Inst. Eng. India Ser. A 96, 37–46 (2015)

    Article  Google Scholar 

  38. H.R. Tizhoosh, Opposition-based learning: a new scheme for machine inteligence, in Computational Intelligence for Modelling, Control and Automation, 2005 and Int. Conf. on Intelligent Agents, Web Technologies and Internet Commerce, IEEE Xplore (2005), pp. 695–701

  39. F. Van Den Bergh, A.P. Engelbrecht, A convergence proof for the particle swarm optimiser. Fund. Inform. 105(4), 341–374 (2010)

    MathSciNet  MATH  Google Scholar 

  40. I.T. Yang, Using elitist particle swarm optimization to facilitate bicriterion time-cost trade-off analysis. J. Constr. Eng. Manag. 133(7), 498–505 (2007)

    Article  Google Scholar 

  41. B. Zahraie, M. Tavakolan, Stochastic time-cost-resource utilization optimization using nondominated sorting genetic algorithm and discrete fuzzy sets. J. Constr. Eng. Manag. 135(11), 1162–1171 (2009)

    Article  Google Scholar 

  42. H. Zhang, H. Li, Multi-objective particle swarm optimization for construction time-cost tradeoff problems. Constr. Manag. Econ. 28(1), 75–88 (2010)

    Article  MathSciNet  Google Scholar 

  43. H. Zheng, The bi-level optimization research for time-cost-quality-environment trade-off scheduling problem and its application to a construction project. Adv. Intell. Syst. Comput. 502, 745–753 (2017)

    Google Scholar 

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Acknowledgement

The authors thankfully recognize the effort of project team for assisting in data preparation.

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  1. Department of Civil Engineering, Madhav Institute of Technology and Science, Gwalior, India

    Kamal Sharma & Manoj Kumar Trivedi

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  1. Kamal Sharma
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  2. Manoj Kumar Trivedi
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Correspondence to Kamal Sharma.

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Sharma, K., Trivedi, M.K. Development of Multi-Objective Scheduling Model for Construction Projects Using Opposition-Based NSGA III. J. Inst. Eng. India Ser. A 102, 435–449 (2021). https://doi.org/10.1007/s40030-021-00529-w

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