Çok Modlu Kaynak Kısıtlı Proje Çizelgeleme Problemlerinin BelirsizlikOrtamında Modellenmesi

Bu çalışmada, belirsizlik ortamında proje süreçlerinin çizelgelenmesine olanak tanıyan bulanık etkinlik sürelerinden oluşan çok modlu, kaynak kısıtlı proje çizelgeleme problemleri incelenmiştir. Proje çizelgeleme problemlerinin çözümü için Microsoft C# programlama dili kullanılarak “Proje Çizelgeleme Programı” olarak isimlendirilen bir paket program geliştirilmiş, literatürde Proje Çizelgeleme Problemleri Kütüphanesi (PSPLib) olarak bilinen örnek problem setleri üzerinde test edilerek çıktı sonuçları kıyaslanmıştır. Kaynak kısıtlı bulanık çok modlu proje çizelgeleme problemleri, geliştirilen program ile çözülerek toplam proje süreleri ve toplam çizelgeleme maliyetleri en küçüklenmektedir.

Multi-Mode Resource Constrained Project Scheduling Under Fuzzy Enviroment

In this paper, we consider multi-mode resource-constrained project scheduling problems with multipleexecution modes for each activity under uncertainty conditions. A software package named as “ProjectScheduling Programming” was developed by using Microsoft C# and its performance was tested onsome sample projects and PSPLib data sets. Project scheduling problems defined with constrainedresources and uncertainty issues can be solved by by Project Scheduling Software in order to minimizetotal project makespan and scheduling cost.

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Atlı, Ö. and Kahraman, C. 2013. Fuzzy critical path analysis, Sigma Journal of Engineering and Natural Science, 31, 128-140.
Atli, Ö. 2011. Tabu search and an exact algorithm for the solutions of resource-constrained project scheduling problems.International Journal of Computational Intelligence Systems, 2, 255-267. https://doi.org/10.1080/18756891.2011.9727781
Arauj, J.S.S., Santos, H.G., Gendron, B., Dominik J.S., Brito, S.S. and Souza, D.S., 2020. Strong bounds for resource constrained project scheduling: Preprocessing and cutting planes. Computers and Operations Research, 113, 104782. https://doi.org/10.1016/j.cor.2019.104782
Birjandi A. and Mousavi S.M., 2019. Fuzzy resourceconstrained project scheduling with multiple routes: A heuristic solution. Automation in Construction, 100, 84–102. https://doi.org/10.1016/j.autcon.2018.11.029
Bouleimen, K. and Lecocq, H. A new efficient simulated annealing algorithm for the resource constrained project scheduling problem. Tech. rep., Service de Robotique et Automatisation, Universite de Liege, 1998.
Bouleimen, K. and Lecocq, H., 2003. A new efficient simulated annealing algorithm for the resourceconstrained project scheduling problem and its multiple mode version. In European Journal of Operational Research, 49(2), 268-281. https://doi.org/10.1016/S0377-2217(02)00761-0
Bofill, M., Coll,J., Suy, J. and Villaret, M. 2020. SMT encodings for Resource-Constrained Project Scheduling Problems. Computers & Industrial Engineering, 149, 106777. https://doi.org/10.1016/j.cie.2020.106777
Buckley, J. J., 1985. Fuzzy Hierarchical Analysis. Fuzzy Sets and Systems, 17(3), 233-247.
Brucker,P., Drexl,A., Möhrıng, R. Neumann,K. and Pesch.E., 1999. Resources-Constrained Project Scheduling: Notation, Classification, Model and Methods. European Journal of Operational Research, 112,. 3-41. https://doi.org/10.1016/S0377-2217(98)00204-5
Chanas, S. and Kamburowski, J., 1981. The use of fuzzy variables in pert. Fuzzy Sets and Systems, 5(1), 11-19. https://doi.org/10.1016/0165-0114(81)90030-0
Chen, S. P. and Hsueh, Y. J., 2008. A simple approach to fuzzy critical path analysis in project networks. Applied Mathematical Modelling, 32(7), 1289-1297. https://doi.org/10.1016/j.apm.2007.04.009
Drexl, A. and Gruenewald, J. 1993. Nonpreemptive multimode resource-constrained project scheduling. IIE transactions, 25(5), 74-81. https://doi.org/10.1080/07408179308964317
Drexl,A., Nıssen R., Patterson J. and Salewskı F. 2000. PROGEN/ πX – An ınstance generator for resourcesconstrained project scheduling problems with partially renewable resources and further extensions. European Journal of Operational Research, 125, 59- 72. https://doi.org/10.1016/S0377-2217(99)00205-2
Dubois, D. and Prade, H., 1988. Possibility theory: An Approach to Computerized Processing of Uncertainty. Computational Complexity. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-1800-9_139
Dubois, D. and Prade, H. 1983. Ranking fuzzy numbers in the setting of possibility theory. Information Sciences, 30(3), 183-224. https://doi.org/10.1016/0020-0255(83)90025-7
Elsayed, E. A., 1982. Algorithms for project scheduling with resource constraints. International Journal of Production Research, 20(1), 95–103. https://doi.org/10.1080/00207548208947751
Glover, F. 1990a. Tabu Search—Part II. ORSA Journal on Computing, 2(1), 4-32. https://doi.org/10.1287/ijoc.2.1.4
Glover, F. 1990b. Tabu Search: A Tutorial. Interfaces, 20(4), 74-94. https://doi.org/10.1287/inte.20.4.74
Hapke, M., Jaszkiewicz, A., and Słowiński, R. 2000. Pareto simulated annealing for fuzzy multi-objective combinatorial optimization. Journal of Heuristics, 6, 29–345. https://doi.org/10.1023/A:1009678314795
Hartmann, S. and Drexl, A. 1998. Project scheduling with multiple modes: A comparison of exact algorithms. Networks: An International Journal, 32(4), 283-297. https://doi.org/10.1002/(SICI)10970037(199812)32: 4<283::AID-NET5>3.0.CO;2-I
Jarboui, B., Damak, N., Siarry, P. and Rebai, A., 2008. A combinatorial particle swarm optimization for solving multi-mode resource-constrained project scheduling problems. Applied Mathematics and Computation, 195(1), 299-308. https://doi.org/10.1016/j.amc.2007.04.096
Kassandraa, T.R. and Suhartonob, D., 2018. ResourceConstrained Project Scheduling Problem using Firefly Algorithm. Procedia Computer Science, 135, 534–543. https://doi.org/10.1016/j.procs.2018.08.206
Knyazevaa, M., Bozhenyuka, A. and Rozenbergb, I. 2015. Resource-constrained project scheduling approach under fuzzy Conditions. Procedia Computer Science 77, 56 – 64. https://doi.org/10.1016/j.procs.2015.12.359
Kulejewski, J., Ibadov, N. and Krzemiński, M. 2018. Scheduling Construction Projects Under Fuzzy Modelling of Resource Constraints. MATEC Web of Conferences, 196, 04045. https://doi.org/10.1051/matecconf/201819604045
Kurt, P.A., 2018. Çok projeli kaynak kısıtlı proje çizelgeleme problemi: bir yazılım firmasında uygulama çalışması (Yüksek lisans), Başkent Üniversitesi Fen Bilimleri Enstitüsü,104.
Mori, M. and Tseng, C.C., 1997. A genetic algorithm for multi mode resource constrained project scheduling problem. European Journal of operational Research. 100, 134-141. https://doi.org/10.1016/S0377- 2217(96)00180-4
Nasution, S. H., 1994. Fuzzy Critical Path Method. IEEE Transactions on Systems, Man and Cybernetics, 24(1), 48-57. https://doi.org/10.1109/21.259685
Özdamar, L. and Ulusoy, G. 1995. A survey on the resource-constrained project scheduling problem. IIE Transactions, 27: 574-586. https://doi.org/10.1080/07408179508936773
Patterson, J. H., 1984. A Comparison of Exact Approaches for Solving the Multiple Constrained Resource, Project Scheduling Problem. Management Science, 30(7), 854-867. https://doi.org/10.1287/mnsc.30.7.854
Pellerin, R., Perrier, N. and Berthaut, F., 2020. A survey of hybrid metaheuristics for the resource-constrained project scheduling problem. European Journal of Operational Research, 280, 395–416. https://doi.org/10.1016/j.ejor.2019.01.063
Rahman, H.F., Chakrabortty, R.K. and Ryan, M.J., 2020 Memetic algorithm for solving resource constrained project scheduling Problems. Automation in Construction, 111, 103052. https://doi.org/10.1016/j.autcon.2019.103052
Sharma, K. and Trivedi, M. K., 2020 Latin hypercube sampling-based NSGA-III optimization model for multimode resource constrained time–cost–quality– safety trade-off in construction projects International Journal of Construction Management (online). https://doi.org/10.1080/15623599.2020.1843769
Talbot, F. B., 1982. Resource-Constrained Project Scheduling with Time-Resource Tradeoffs: The Nonpreemptive Case. Management Science, 28(10), 1197-1210. https://doi.org/10.1287/mnsc.28.10.1197
Wang, X., and Huang, W., 2010. Fuzzy resourceconstrained project scheduling problem for software development. Wuhan University Journal of Natural Sciences, 15(1), 25-30. https://doi.org/10.1007/s11859-010-0106-z
Weglarz,J, 1980. On certain models of resource allocation, problems, Kybernetes 9, 61-66.
Yager, R. R., 1981. A procedure for ordering fuzzy subsets of the unit interval. Information Sciences, 24(2), 143- 161. https://doi.org/10.1016/0020-0255(81)90017-7
Zadeh, L. A., 1965. Fuzzy Sets. Information and Control, 8(3), 338-353. https://doi.org/10.1109/2.53
Zaman, F., Elsayed, F., Sarker, R., Essam, D. 2020. Hybrid evolutionary algorithm for large-scale project scheduling problems. Computers & Industrial Engineering, 146, 106567. https://doi.org/10.1016/j.cie.2020.106567
Zaman,F., Elsayed,S., Sarker, R., Essam, D., Carlos A. Coello C. 2021. An evolutionary approach for resource constrained project scheduling with uncertain changes. Computers and Operations Research, 125, 105104. https://doi.org/10.1016/j.cor.2020.105104
Zimmermann, H.-J., 2001. Fuzzy Relations and Fuzzy Graphs. In Fuzzy Set Theory—and Its Applications, 321-367. https://doi.org/10.1007/978-94-010-0646-0_6
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