Yıl: 2019 Cilt: 9 Sayı: 2 Sayfa Aralığı: 208 - 215 Metin Dili: İngilizce DOI: 10.11121/ijocta.01.2019.00631 İndeks Tarihi: 15-11-2019

Credibility based chance constrained programming for project scheduling with fuzzy activity durations

Öz:
This paper proposes a credibility based chance constrained programmingapproach for project scheduling problems with fuzzy activity durations where theobjective is to minimize the fuzzy project completion time. This paper expressesthe fuzzy events such as a project activity’s duration or project completion timewith fuzzy chance constraints and the chance of a fuzzy event is illustrated withfuzzy credibility distribution. Due to uncertainty in durations of a project, fuzzysets and fuzzy numbers can be used in order to illustrate the uncertainty and finda solution space for the problem. Therefore, fuzzy credibility based chanceconstraint technique is investigated for project scheduling problems with fuzzyactivity durations considering the uncertainty or chance of a fuzzy event within aclosed interval. In this paper, a fuzzy mathematical model and its crispequivalent by using credibility measure and chance-constrained programming aregiven for project scheduling problems with fuzzy activity durations.
Anahtar Kelime:

Konular: Matematik İstatistik ve Olasılık
Belge Türü: Makale Makale Türü: Araştırma Makalesi Erişim Türü: Erişime Açık
  • DePorter, E. L., & Ellis, K. P. (1990). Optimization of project networks with goal programming and fuzzy linear programming. Computers and Industrial Engineering, 19(1–4), 500–504.
  • Bonnal, P., Gourc, D., & Lacoste, G. (2004). Where do we stand with fuzzy project scheduling? Journal of Construction Engineering and Management, 130(1), 114–123.
  • Herroelen, W., & Leus, R. (2005). Project scheduling under uncertainty: Survey and research potentials. European Journal of Operational Research, 165(2), 289–306.
  • Hapke, M., Jaszkiewicz, A., & Slowinski, R. (1994). Fuzzy project scheduling system for software development. Fuzzy Sets and Systems, 67(1), 101–117.
  • Hapke, M., & Slowinski, R. (1996). Fuzzy priority heuristics for project scheduling. Fuzzy Sets and Systems, 83(3), 291–299.
  • Wang, H.-F., & Fu, C.-C. (1996). Fuzzy project scheduling models under inflation condition. International Journal of Uncertainty, Fuzziness and Knowlege-Based Systems, 4(6), 497–514.
  • Hapke, M., Jaszkiewicz, A., & Slowinski, R. (1997). Fuzzy project scheduling with multiple criteria. In IEEE International Conference on Fuzzy Systems, 3, 1277–1282.
  • Özdamar, L., & Alanya, E. (2001). Uncertainty Modelling in Software Development Projects (With Case Study). Annals of Operations Research, 102(1–4), 157–178.
  • Wang, J. (2002). A fuzzy project scheduling approach to minimize schedule risk for product development. Fuzzy Sets and Systems, 127(2), 99–116.
  • Chanas, S., Dubois, D., & Zieliński, P. (2002). On the sure criticality of tasks in activity networks with imprecise durations. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 32(4), 393–407.
  • Chanas, S., & Zieliński, P. (2003). On the hardness of evaluating criticality of activities in a planar network with duration intervals. Operations Research Letters, 31(1), 53–59.
  • Pan, H., & Yeh, C.-H. (2003). Fuzzy project scheduling. In IEEE International Conference on Fuzzy Systems, 1, 755–760.
  • Pan, H., & Yeh, C.-H. (2003). A metaheuristic approach to fuzzy project scheduling. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 2773 PART, 1081–1087.
  • Wang, J. (2004). A fuzzy robust scheduling approach for product development projects. European Journal of Operational Research, 152(1), 180–194.
  • Ke, H., & Liu, B. (2004). Project scheduling problem with fuzzy activity duration times. In IEEE International Conference on Fuzzy Systems, 2, 819–823.
  • Zieliński, P. (2005). On computing the latest starting times and floats of activities in a network with imprecise durations. Fuzzy Sets and Systems, 150(1), 53–76.
  • Agarwal, R., Tiwari, M. K., & Mukherjee, S. K. (2007). Artificial immune system based approach for solving resource constraint project scheduling problem. International Journal of Advanced Manufacturing Technology, 34(5–6), 584–593.
  • Ke, H., & Liu, B. (2007). Project scheduling problem with mixed uncertainty of randomness and fuzziness. European Journal of Operational Research, 183(1), 135–147.
  • Long, L. D., & Ohsato, A. (2008). Fuzzy critical chain method for project scheduling under resource constraints and uncertainty. International Journal of Project Management, 26(6), 688–698.
  • Huang, W., Ding, L., Wen, B., & Cao, B. (2009). Project scheduling problem for software development with random fuzzy activity duration times. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 5552.
  • Moradi, M., Hafezalkotob, A., & Ghezavati, V. (2018). Sustainability in fuzzy resource constraint project scheduling in a cooperative environment under uncertainty: Iran’s Chitgar lake case study. Journal of Intelligent and Fuzzy Systems, 35(6), 6255–6267.
  • Hu, C., & Liu, D. (2018). Improved Critical Path Method with Trapezoidal Fuzzy Activity Durations. Journal of Construction Engineering and Management, 144(9).
  • Zhang, Q., Zhou, J., Wang, K., & Pantelous, A. A. (2018). An Effective Solution Approach to Fuzzy Programming with Application to Project Scheduling. International Journal of Fuzzy Systems, 20(8), 2383–2398.
  • Zhang, X., Hipel, K. W., & Tan, Y. (2019). Project portfolio selection and scheduling under a fuzzy environment. Memetic Computing.
  • Castro-Lacouture, D., Süer, G. A., Gonzalez- Joaqui, J., & Yates, J. K. (2009). Construction project scheduling with time, cost, and material restrictions using fuzzy mathematical models and critical path method. Journal of Construction Engineering and Management, 135(10), 1096– 1104.
  • Afshar, A., & Fathi, H. (2009). Fuzzy multi- objective optimization of finance-based scheduling for construction projects with uncertainties in cost. Engineering Optimization, 41(11), 1063–1080.
  • Shi, Q., & Gong, T. (2009). An improved project buffer sizing approach to critical chain management under resources constraints and fuzzy uncertainty. In 2009 International Conference on Artificial Intelligence and Computational Intelligence, AICI 2009, 1,486–490.
  • Wang, X., & Huang, W. (2010). Fuzzy resource- constrained project scheduling problem for software development. Wuhan University Journal of Natural Sciences, 15(1),25–30.
  • Bhaskar, T., Pal, M. N., & Pal, A. K. (2011). A heuristic method for RCPSP with fuzzy activity times. European Journal of Operational Research, 208(1),57–66. Ponz-Tienda, J. L., Pellicer, E., & Yepes, V. (2012). Complete fuzzy scheduling and fuzzy earned value management in construction projects. Journal of Zhejiang University: Science A, 13(1), 56–68.
  • Maravas, A., & Pantouvakis, J.-P. (2012). Project cash flow analysis in the presence of uncertainty in activity duration and cost. International Journalof Project Management, 30(3), 374–384.
  • Xu, J., & Zhang, Z. (2012). A fuzzy random resource-constrained scheduling model with multiple projects and its application to a working procedure in a large-scale water conservancy and hydropower construction project. Journal of Scheduling, 15(2),253–272.
  • Masmoudi, M., & Haït, A. (2013). Project scheduling under uncertainty using fuzzy modelling and solving techniques. Engineering Applications of Artificial Intelligence, 26(1),135–149.
  • Huang, W., Oh, S.-K., & Pedrycz, W. (2013). A fuzzy time-dependent project scheduling problem. Information Sciences, 246,100–114.
  • Chrysafis, K. A., & Papadopoulos, B. K. (2015). Possibilistic moments for the task duration in fuzzy PERT. Journal of Management in Engineering, 31(5).
  • Huang, X., Dai, W., & Du, B. (2016). Resource- constrained project scheduling problem for large complex equipment: A hybrid approach using pareto genetic algorithm and interval-valued intuitionistic fuzzy sets. Academic Journal of Manufacturing Engineering, 14(1),12–21.
  • Yu, M.-C., Dang, V.-L., & Yeh, H.-C. (2017). Measuring cash flow and overdraft for fuzzy project networks with overlapping activities. Journal of Civil Engineering and Management, 23(4),487–498.
  • Yousefli, A. (2017). A fuzzy ant colony approach to fully fuzzy resource constrained project scheduling problem. Industrial Engineering and Management Systems, 16(3),307–315.
  • Zohoori, B., Verbraeck, A., Bagherpour, M., & Khakdaman, M. (2019). Monitoring production time and cost performance by combining earned value analysis and adaptive fuzzy control. Computers and Industrial Engineering, 127, 805– 821.
  • Habibi, F., Barzinpour, F., & Sadjadi, S. J. (2019). A mathematical model for project scheduling and material ordering problem with sustainability considerations: A case study in Iran. Computers and Industrial Engineering, 128,690–710.
  • Alipouri, Y., Sebt, M. H., Ardeshir, A., & Chan,W. T. (2019). Solving the FS-RCPSP with hyper- heuristics: A policy-driven approach. Journal of the Operational Research Society, 70(3), 403–419.
  • Birjandi, A., & Mousavi, S. M. (2019). Fuzzy resource-constrained project schedulingwith multiple routes: A heuristic solution. Automation in Construction, 100, 84–102.
  • Toksarı, M. D., & Arık, O. A. (2017). Single machine scheduling problems under position- dependent fuzzy learning effect with fuzzy processing times. Journal of Manufacturing Systems, 45,159–179.
  • Arık, O. A., & Toksarı, M. D. (2018). Multi- objective fuzzy parallel machine scheduling problems under fuzzy job deterioration and learning effects. International Journal of Production Research, 56(7),2488–2505.
  • Arık, O. A., & Toksarı, M. D. (2018). Fuzzy chance constrained programming technique for single machine earliness/tardiness scheduling problem under effects of fuzzy learning and deterioration. Sakarya University Journal of Science, 22(2),1–1.
  • Zadeh, L. A. (1978). Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems, 1(1), 3–28.
  • Liu, B., & Liu, Y. (2002). Expected value of fuzzy variable and fuzzy expected value models.IEEE Transactions on Fuzzy Systems, 10(4), 445–450.
  • Liu, B. (2002). Theory and Practice ofUncertain Programming (2nd ed.). Heidelberg: Springer- VerlagBerlin.
  • Charnes, A., & Cooper, W. W. (1959). Chance- Constrained Programming. Management Science, 6(1),73–79.
  • Liu, B., & Iwamura, K. (1998). Chance constrained programming with fuzzy parameters. Fuzzy Sets and Systems, 94(2), 227–237.
APA Arık O (2019). Credibility based chance constrained programming for project scheduling with fuzzy activity durations. , 208 - 215. 10.11121/ijocta.01.2019.00631
Chicago Arık Oğuzhan Ahmet Credibility based chance constrained programming for project scheduling with fuzzy activity durations. (2019): 208 - 215. 10.11121/ijocta.01.2019.00631
MLA Arık Oğuzhan Ahmet Credibility based chance constrained programming for project scheduling with fuzzy activity durations. , 2019, ss.208 - 215. 10.11121/ijocta.01.2019.00631
AMA Arık O Credibility based chance constrained programming for project scheduling with fuzzy activity durations. . 2019; 208 - 215. 10.11121/ijocta.01.2019.00631
Vancouver Arık O Credibility based chance constrained programming for project scheduling with fuzzy activity durations. . 2019; 208 - 215. 10.11121/ijocta.01.2019.00631
IEEE Arık O "Credibility based chance constrained programming for project scheduling with fuzzy activity durations." , ss.208 - 215, 2019. 10.11121/ijocta.01.2019.00631
ISNAD Arık, Oğuzhan Ahmet. "Credibility based chance constrained programming for project scheduling with fuzzy activity durations". (2019), 208-215. https://doi.org/10.11121/ijocta.01.2019.00631
APA Arık O (2019). Credibility based chance constrained programming for project scheduling with fuzzy activity durations. An International Journal of Optimization and Control: Theories & Applications (IJOCTA), 9(2), 208 - 215. 10.11121/ijocta.01.2019.00631
Chicago Arık Oğuzhan Ahmet Credibility based chance constrained programming for project scheduling with fuzzy activity durations. An International Journal of Optimization and Control: Theories & Applications (IJOCTA) 9, no.2 (2019): 208 - 215. 10.11121/ijocta.01.2019.00631
MLA Arık Oğuzhan Ahmet Credibility based chance constrained programming for project scheduling with fuzzy activity durations. An International Journal of Optimization and Control: Theories & Applications (IJOCTA), vol.9, no.2, 2019, ss.208 - 215. 10.11121/ijocta.01.2019.00631
AMA Arık O Credibility based chance constrained programming for project scheduling with fuzzy activity durations. An International Journal of Optimization and Control: Theories & Applications (IJOCTA). 2019; 9(2): 208 - 215. 10.11121/ijocta.01.2019.00631
Vancouver Arık O Credibility based chance constrained programming for project scheduling with fuzzy activity durations. An International Journal of Optimization and Control: Theories & Applications (IJOCTA). 2019; 9(2): 208 - 215. 10.11121/ijocta.01.2019.00631
IEEE Arık O "Credibility based chance constrained programming for project scheduling with fuzzy activity durations." An International Journal of Optimization and Control: Theories & Applications (IJOCTA), 9, ss.208 - 215, 2019. 10.11121/ijocta.01.2019.00631
ISNAD Arık, Oğuzhan Ahmet. "Credibility based chance constrained programming for project scheduling with fuzzy activity durations". An International Journal of Optimization and Control: Theories & Applications (IJOCTA) 9/2 (2019), 208-215. https://doi.org/10.11121/ijocta.01.2019.00631