Effects of Project Uncertainties on Nonlinear Time-Cost Tradeoff Profile

Document Type : Research Paper

Authors

1 Department of Mathematics, Jaypee University, Anoop- shahr, Bulandshahr, 203390 India

2 Department of Mechanical Engineering, Dayalbagh Educational Institute (Deemed University), Dayalbagh, Agra, 282005 India

Abstract

This study presents the effects of project uncertainties on nonlinear time-cost tradeoff (TCT) profile of real life engineering projects by the fusion of fuzzy logic and artificial neural network (ANN) models with hybrid meta-heuristic (HMH) technique, abridged as Fuzzy-ANN-HMH. Nonlinear time-cost relationship of project activities is dealt with ANN models. ANN models are then integrated with HMH technique to search for Pareto-optimal nonlinear TCT profile. HMH technique incorporates simulated annealing in the selection process of multiobjective genetic algorithm. Moreover, in real life engineering projects, uncertainties like management experience, labor skills, and weather conditions are commonly involved, which affect the duration and cost of the project activities. Fuzzy-ANN-HMH analyses responsiveness of nonlinear TCT profile with respect to these uncertainties. A comparison of Fuzzy-ANN-HMH is made with another method in literature to solve nonlinear TCT problem and the superiority of Fuzzy-ANN-HMH is demonstrated by results. The study gives project planners to carry out the best plan that optimizes time and cost to complete a project under uncertain environment.

Keywords

References

[1] M. V. Arias and C. A. C. Coello, Asymptotic convergence of metaheurisitcs for multiobjective
optimization problems, Soft Comput., 10 (2005), 1001{1005.
[2] S. P. Chen, M. J. Tsai, Time-cost trade-o analysis of project networks in fuzzy environments,
Eur. J. Oper.Res., 212(2) (2011), 386{397.
[3] K. Deb, Multi-objective optimization using evolutionary algorithms, NewYork: JohnWiley
and Sons, 2001.
[4] E. Eshtehardian, A. Afshar and R. Abbasnia, Fuzzy-based MOGA approach to stochastic
time cost trade-o problem, Automation in Construction, 18 (2009), 692{701.
[5] L. Fausett, \Fundamentals of neural networks," NJ: Prentice Hall Englewood Cli s, 1994.
[6] C. W. Feng, L. Liu, and S. A. Burns, Using genetic algorithms to solve construction time-cost
trade-o problems, J. Comput. Civil Eng., 11 (1997), 184{189.
[7] H. Ke, W. Ma, X. Gao and W. Xu, New fuzzy models for time-cost trade-o problem, Fuzzy
Optim Decis Making, 9 (2010), 219{231.
[8] S. Kirkpatrick, C. D. Gelatt and M. P. Vecchi, Optimization by simulated annealing, Sci.,
220 (1983), 671{680.
[9] S. S. Leu, A. T. Chen and C. H. Yang, A GA-based fuzzy optimal model for construction
time-cost trade-o , Int. J. Project Manage., 19 (2001), 47{58.
[10] L. Liu, S. Burns and C. Feng, Construction time-cost trade-o analysis using LP/IP hybrid
method, J. Const. Eng. Manage., 121(4) (1995), 446{454.
[11] E. H. Mamdani, Application of fuzzy logic to approximate reasoning using linguistic synthesis,
Trans. Comput., 26(12) (1977), 1182{1191.
[12] E. H. Mamdani, Applications of fuzzy algorithms for control of simple dynamic plant, In:
Proc. IEEE, 121(12) (1974), 1585{1588.
[13] B. K. Pathak and S. Srivastava, Integrated Fuzzy-HMH for project uncertainties in time-cost
tradeo problem, Applied Soft Computing, 21 (2014), 320-329.
[14] B. K. Pathak and S. Srivastava, MOGA based time-cost tradeo s: responsiveness for project
uncertainties, In: Proc. CEC, (2007), 3085{3092.
[15] B. K. Pathak, S. Srivastava and K. Srivastava, Neural network embedded multiobjective ge-
netic algorithm to solve nonlinear time-cost tradeo problems of project scheduling, J. Sci.
Ind. Res., 67(2) (2008), 124{131.
[16] S. Srivastava, B. Pathak and K. Srivastava, Project scheduling: time-cost tradeo problems,
In: Comput. Intell.Optimization, Y. Tenne and C-K Goh Ed., Springer-Verlag Berlin Heidel-
berg, 7 (2010), 325{357.
[17] S. Srivastava, K. Srivastava, R. S. Sharma and K. H. Raj, Modelling of hot closed die forging
of an automotive piston with ANN for intelligent manufacturing, J. Sci. Ind. Res., 63 (2004),
997{1005.
[18] M. O. Suliman, V. S. S. Kumar and W. Abdulal, Optimization of uncertain construction time-
cost trade o problem using simulated annealing algorithm, World Congr. Inform. Commun.
Tech., (2011), 489{494.
[19] L. A. Zadeh, Fuzzy sets, Inform. and Control, 8(3) (1965), 333{353.
[20] L. A. Zadeh, Outline of a New Approach to the Analysis of a Complex System and Decision
Processes, IEEE Trans. Syst. Man Cybern., 3 (1973), 28{44.
Iranian Journal of Fuzzy Systems
Volume 12, Issue 4 - Serial Number 4
July and August 2015
Pages 79-100

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