Abstract

In the present paper, Characteristics of fuzzy project network using statistical data are discussed in detail in order to calculate the fuzzy critical path, fuzzy earliest times, fuzzy latest times and fuzzy total float. Fuzzy number as fuzzy activity time is constructed using interval estimate by calculating mean, variance and standard error. A new ranking function is used to discriminate the fuzzy numbers used as activity times in the fuzzy project network and used it in distance measure. The appropriateness and contribution of characteristics of fuzzy project network to ship building is discussed and calculated as an application to real life problem using statistical parameters.

References

• Gazdik, I. (1983). Fuzzy network planning – FNET. IEEE Transactions on Reliability, 32, 304–313. doi:10. 1109/TR. 1983. 5221657.
• Chang, D. H. , Son, J. H. , & Kim, M. H. (2002). Criti¬cal path identification in the context of a workflow. Information and Software Technology, 44, 405–417. doi:10. 1016/S0950-5849(02)00025-3.
• Chang, I. S. , Tsujimura, Y. , Gen, M. , & Tozawa, T. (1995). An efficient approach for large scale proj¬ect Planning based on fuzzy delphi method. Fuzzy Sets and Systems, 76, 277–288. doi:10. 1016/0165-0114(94)00385- 4.
• Hapke, M. , Jaszkiewicz, A. , & Slowinski, R. (1994). Fuzzy project scheduling system for software de-velopment. Fuzzy Sets and Systems, 67, 101–117. doi:10. 1016/0165-0114(94)90211-9.
• Lorterapong, P. (1994). A fuzzy heuristic method for resource constrained project scheduling. Project Management Journal, 25, 12–18.
• Chen, Y. L. , Rinks, D. & Tang, K. (1997). Critical path in an activity network with time constraints. European Journal of Operational Research, 100, 122–133. doi:10. 1016/S0377-2217(96)00140-3.
• Yao, J. S. , & Lin, F. T. (2000). Fuzzy critical path method based on signed distance ranking of fuzzy numbers. IEEE Transactions on Systems, Man, and Cybernetics. Part A, Systems and Humans, 30, 76–82. Doi:10. 1109/TSMCA. 2000. 833106.
• Chen, L. H. , & Lu, H. W. (2001). An approximate approach for ranking fuzzy numbers based on left and right dominance. Computers & Mathematics with Applications (Oxford, England),41,1589–1602. doi:10. 1016/S0898- 1221(01)00124-9.
• Lin, F. T. (2001). Critical path method in activity networks with fuzzy activities duration times. Pro¬ceedings IEEE Conference on Systems, Man and Cybernetics, 2, 1155- 1160.
• Lin, F. T. (2002). Fuzzy critical path method based on statistical data. Proceedings IEEE International Conference on Fuzzy Systems, 2, 1245-1250.
• Lin, F. T. , & Yao, J. S. (2003). Fuzzy critical path method based on signed distance ranking and statistical confidence interval estimates. The Journal of Supercomputing, 24, 305–325. doi:10. 1023/A:1022036931014.
• Zielinski, P. (2005). On computing the latest start¬ing times and floats of activities in a network with imprecise durations. Fuzzy Sets and Systems, 150, 53–76. doi:10. 1016/j. fss. 2004. 08. 007.
• Tian, F. , & Li, R. (2006). A fuzzy critical path method based scheduling approach for collaboration process. In Proceedings 10th International Confer¬ence on Computer Supported Cooperative Work in Design (pp. 1-6).
• Chen, S. P. , & Hsueh, Y. J. (2008). A simple approach to fuzzy critical path analysis in project networks. Applied Mathematical Modelling, 32, 1289–1297. doi:10. 1016/j. apm. 2007. 04. 009.
• Yakhchali, S. H. , Ghodsypour, S. H. , & Fatemi Ghomi, S. (2008). An incremental approach for temporal analysis in networks with imprecise ac¬tivity and time lag durations. In Proceedings IEEE International Conference on Industrial Engineering and Engineering Management (pp. 1774-1778).
• Lin, F. T. (2008). Time-cost trade off in fuzzy critical path analysis based on (1-?) × 100% confidence-interval estimates. In Proceedings IEEE International Conference on Systems, Man and Cybernetics (pp. 601-606).
• Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353. doi:10. 1016/S0019- 9958(65)90241-X.
• Chen LS, Cheng CH (2005) Selecting IS personnel using ranking fuzzy number by metric distance method. European Journal of Operational research 160 (3) : 803- 820.
• N. Ravi Shankar, V. Sireesha, K. Srinivasa Rao and N. Vani. Fuzzy Critical Path Method Based on MetricDistanceRanking of Fuzzy Numbers Int. Journal of Math. Analysis, Vol. 4, 2010, no. 20, 995 – 1006.
• Jin-Shing Yao and Feng –Tse Lin. IEEE transactions systems, man and cybernetics –part A: Systems and Humans ,vol. 30,no,1,January 2000