179
Views
0
CrossRef citations to date
0
Altmetric
Research Article

A robust chance-constrained programming approach for a bi-objective pre-emptive multi-mode resource-constrained project scheduling problem with time crashing

ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon & ORCID Icon
Article: 2253147 | Received 02 Feb 2023, Accepted 23 Aug 2023, Published online: 13 Sep 2023

References

  • Abdel-Basset, M., Ali, M., & Atef, A. (2020). Uncertainty assessments of linear time-cost tradeoffs using neutrosophic set. Computers & Industrial Engineering, 141(1), 106286. https://doi.org/10.1016/j.cie.2020.106286
  • Afshar, M. R., Shahhosseini, V., & Sebt, M. H. (2019). A genetic algorithm with a new local search method for solving the multimode resource-constrained project scheduling problem. International Journal of Construction Management, 22(3), 1–9. https://doi.org/10.1080/15623599.2019.1623992
  • Afshar-Nadjafi, B. (2018). A solution procedure for preemptive multi-mode project scheduling problem with mode changeability to resumption. Applied Computing and Informatics, 14(2), 192–201. https://doi.org/10.1016/j.aci.2014.02.003
  • Ameri, Z., Sana, S. S., & Sheikh, R. (2019). Self-assessment of parallel network systems with intuitionistic fuzzy data: A case study. Soft Computing, 23(23), 12821–12832. https://doi.org/10.1007/s00500-019-03835-5
  • Aouam, T., & Vanhoucke, M. (2019). An agency perspective for multi-mode project scheduling with time/cost trade-offs. Computers & Operations Research, 105(1), 167–186. https://doi.org/10.1016/j.cor.2019.01.012
  • Aramesh, S., Mousavi, S. M., Ghasemi, M., & Shahabi-Shahmiri, R. (2022). An optimization model for construction project scheduling by considering CO2 emissions with multi-mode resource constraints under interval-valued fuzzy uncertainty. International Journal of Environmental Science and Technology, 20(1), 1–16. https://doi.org/10.1007/s13762-022-04377-4
  • Ballesteros-Perez, P., Elamrousy, K. M., & González-Cruz, M. C. (2019). Non-linear time-cost trade-off models of activity crashing: Application to construction scheduling and project compression with fast-tracking. Automation in Construction, 97(1), 229–240. https://doi.org/10.1016/j.autcon.2018.11.001
  • Balouka, N., & Cohen, I. (2021). A robust optimization approach for the multi-mode resource-constrained project scheduling problem. European Journal of Operational Research, 291(2), 457–470. https://doi.org/10.1016/j.ejor.2019.09.052
  • Banihashemi, S. A., Khalilzadeh, M., Shahraki, A., Malkhalifeh, M. R., & Ahmadizadeh, S. S. R. (2020). Optimization of environmental impacts of construction projects: A time–cost–quality trade-off approach. International Journal of Environmental Science and Technology, 18(3), 1–16. https://doi.org/10.1007/s13762-020-02838-2
  • Behroozi, F., Hosseini, S. M. H., & Sana, S. S. (2021). Teaching–learning-based genetic algorithm (TLBGA): An improved solution method for continuous optimization problems. International Journal of System Assurance Engineering and Management, 12(6), 1362–1384. https://doi.org/10.1007/s13198-021-01319-0
  • Chakrabortty, R. K., Sarker, R. A., & Essam, D. L. (2016). Multi-mode resource constrained project scheduling under resource disruptions. Computers & Chemical Engineering, 88(1), 13–29. https://doi.org/10.1016/j.compchemeng.2016.01.004
  • Chaleshtarti, A. S., Shadrokh, S., Khakifirooz, M., Fathi, M., & Pardalos, P. M. (2020). A hybrid genetic and Lagrangian Relaxation algorithm for resource-constrained project scheduling under nonrenewable resources. Applied Soft Computing, 94(1), 106482. https://doi.org/10.1016/j.asoc.2020.106482
  • Chen, S. H., & Chang, S. M. (2008). Optimization of fuzzy production inventory model with unrepairable defective products. International Journal of Production Economics, 113(2), 887–894. https://doi.org/10.1016/j.ijpe.2007.11.004
  • Creemers, S. (2019). The preemptive stochastic resource-constrained project scheduling problem. European Journal of Operational Research, 277(1), 238–247. https://doi.org/10.1016/j.ejor.2019.02.030
  • Davari, M., & Demeulemeester, E. (2019). Important classes of reactions for the proactive and reactive resource-constrained project scheduling problem. Annals of Operations Research, 274(1), 187–210. https://doi.org/10.1007/s10479-018-2899-7
  • Delgoshaei, A., Rabczuk, T., Ali, A., & Ariffin, M. K. A. (2017). An applicable method for modifying over-allocated multi-mode resource constraint schedules in the presence of preemptive resources. Annals of Operations Research, 259(1), 85–117. https://doi.org/10.1007/s10479-016-2336-8
  • Dixit, V., & Tiwari, M. K. (2020). Project portfolio selection and scheduling optimization based on risk measure: A conditional value at risk approach. Annals of Operations Research, 285(1), 9–33. https://doi.org/10.1007/s10479-019-03214-1
  • Du, B., Tan, T., Guo, J., Li, Y., & Guo, S. (2021). Energy-cost-aware resource-constrained project scheduling for complex product system with activity splitting and recombining. Expert Systems with Applications, 173(1), 114754. https://doi.org/10.1016/j.eswa.2021.114754
  • Elloumi, S., Fortemps, P., & Loukil, T. (2017). Multi-objective algorithms to multi-mode resource-constrained projects under mode change disruption. Computers & Industrial Engineering, 106(1), 161–173. https://doi.org/10.1016/j.cie.2017.01.029
  • Falkerson, D. R. (1961). A network-flow computation for project cost curve. Management Science, 7(2), 167–178. https://doi.org/10.1287/mnsc.7.2.167
  • Ghasemi, M., Mousavi, S. M., Aramesh, S., Shahabi-Shahmiri, R., Zavadskas, E. K., & Antucheviciene, J. (2022). A new approach for production project scheduling with time-cost-quality trade-off considering multi-mode resource-constraints under interval uncertainty. International Journal of Production Research, 61(9), 1–23. https://doi.org/10.1080/00207543.2022.2074322
  • Ghoddousi, P., Eshtehardian, E., Jooybanpour, S., & Javanmardi, A. (2013). Multi-mode resource-constrained discrete time–cost-resource optimization in project scheduling using non-dominated sorting genetic algorithm. Automation in Construction, 30(1), 216–227. https://doi.org/10.1016/j.autcon.2012.11.014
  • Günay, E. E., Kremer, G. E. O., & Zarindast, A. (2020). A multi-objective robust possibilistic programming approach to sustainable public transportation network design. Fuzzy Sets and Systems, 422(1), 106–129. https://doi.org/10.1016/j.fss.2020.09.007
  • Hartmann, S., & Briskorn, D. (2021). An updated survey of variants and extensions of the resource-constrained project scheduling problem. European Journal of Operational Research, 297(1), 1–14. https://doi.org/10.1016/j.ejor.2021.05.004
  • Hasani, A., Hosseini, S. M. H., & Sana, S. S. (2022). Scheduling in a flexible flow shop with unrelated parallel machines and machine-dependent process stages: Trade-off between Makespan and production costs. Sustainability Analytics and Modeling, 2(1), 100010. https://doi.org/10.1016/j.samod.2022.100010
  • Hosseini, S. M. H., Behroozi, F., & Sana, S. S. (2023). Multi-objective optimization model for blood supply chain network design considering cost of shortage and substitution in disaster. RAIRO-Operations Research, 57(1), 59–85. https://doi.org/10.1051/ro/2022206
  • Hosseini, S. M. H., Sana, S. S., & Rostami, M. (2022). Assembly flow shop scheduling problem considering machine eligibility restrictions and auxiliary resource constraints. International Journal of Systems Science: Operations & Logistics, 9(4), 512–528. https://doi.org/10.1080/23302674.2021.1942586
  • Javanmard, S., Afshar-Nadjafi, B., & Niaki, S. T. A. (2017). Preemptive multi-skilled resource investment project scheduling problem: Mathematical modelling and solution approaches. Computers & Chemical Engineering, 96(1), 55–68. https://doi.org/10.1016/j.compchemeng.2016.11.001
  • Kim, J., Kang, C., & Hwang, I. (2012). A practical approach to project scheduling: Considering the potential quality loss cost in the time–cost tradeoff problem. International Journal of Project Management, 30(2), 264–272. https://doi.org/10.1016/j.ijproman.2011.05.004
  • Kolisch, R., & Sprecher, A. (1997). PSPLIB – a project scheduling problem library: OR software-ORSEP operations research software exchange program. European Journal of Operational Research, 96(1), 205–216. https://doi.org/10.1016/S0377-2217(96)00170-1
  • Kopanos, G. M., Kyriakidis, T. S., & Georgiadis, M. C. (2014). New continuous-time and discrete-time mathematical formulations for resource-constrained project scheduling problems. Computers & Chemical Engineering, 68(1), 96–106. https://doi.org/10.1016/j.compchemeng.2014.05.009
  • Kyriakidis, T. S., Kopanos, G. M., & Georgiadis, M. C. (2012). MILP formulations for single- and multi-mode resource-constrained project scheduling problems. Computers & Chemical Engineering, 36(1), 369–385. https://doi.org/10.1016/j.compchemeng.2011.06.007
  • Liu, B. (2002). Toward fuzzy optimization without mathematical ambiguity. Fuzzy Optimization and Decision Making, 1(1), 43–63. https://doi.org/10.1023/A:1013771608623
  • Mahapatra, D. R., Panda, S., & Sana, S. S. (2020). Multi-choice and stochastic programming for transportation problem involved in supply of foods and medicines to hospitals with consideration of logistic distribution. RAIRO-Operations Research, 54(4), 1119–1132. https://doi.org/10.1051/ro/2019050
  • Mavrotas, G. (2009). Effective implementation of the ϵ-constraint method in Multi-Objective Mathematical Programming problems. Applied Mathematics and Computation, 213(2), 455–465. http://doi.org/10.1016/j.amc.2009.03.037
  • Mavrotas, G., & Florios, K. (2013). An improved version of the augmented ϵ-constraint method (AUGMECON2) for finding the exact pareto set in multi-objective integer programming problems. Applied Mathematics and Computation, 219(18), 9652–9669. https://doi.org/10.1016/j.amc.2013.03.002
  • Men, J., Jiang, P., & Xu, H. (2019). A chance constrained programming approach for HazMat capacitated vehicle routing problem in type-2 fuzzy environment. Journal of Cleaner Production, 237(2), 117754. https://doi.org/10.1016/j.jclepro.2019.117754
  • Mirnezami, S. A., Mousavi, S. M., & Mohagheghi, V. (2020). A new interval type-2 fuzzy approach for multi-scenario project cash flow assessment based on alternative queuing method and dependency structure matrix with a case study. Engineering Applications of Artificial Intelligence, 95(1), 103815. https://doi.org/10.1016/j.engappai.2020.103815
  • Muritiba, A. E. F., Rodrigues, C. D., & da Costa, F. A. (2018). A path-relinking algorithm for the multi-mode resource-constrained project scheduling problem. Computers & Operations Research, 92(1), 145–154. https://doi.org/10.1016/j.cor.2018.01.001
  • Pishvaee, M. S., Razmi, J., & Torabi, S. A. (2012). Robust possibilistic programming for socially responsible supply chain network design: A new approach. Fuzzy Sets and Systems, 206(1), 1–20. https://doi.org/10.1016/j.fss.2012.04.010
  • Ranjbar, M., Nasiri, M. M., & Torabi, S. A. (2022). Multi-mode project portfolio selection and scheduling in a build-operate-transfer environment. Expert Systems with Applications, 189(1), 116134. https://doi.org/10.1016/j.eswa.2021.116134
  • Sajadi, S. M., Azimi, P., Ghamginzadeh, A., & Rahimzadeh, A. (2017). A new fuzzy multi-objective multi-mode resource-constrained project scheduling model. International Journal of Mathematics in Operational Research, 11(1), 45–66. https://doi.org/10.1504/IJMOR.2017.085379
  • Schnell, A., & Hartl, R. F. (2016). On the efficient modeling and solution of the multi-mode resource-constrained project scheduling problem with generalized precedence relations. OR Spectrum, 38(2), 283–303. https://doi.org/10.1007/s00291-015-0419-6
  • Sharma, K., & 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, 22(16), 1–11. https://doi.org/10.1080/15623599.2020.1843769
  • Sonmez, R., Iranagh, M. A., & Uysal, F. (2016). Critical sequence crashing heuristic for resource-constrained discrete time–cost trade-off problem. Journal of Construction Engineering and Management, 142(3), 04015090. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001077
  • Subulan, K. (2020). An interval-stochastic programming-based approach for a fully uncertain multi-objective and multi-mode resource investment project scheduling problem with an application to ERP project implementation. Expert Systems with Applications, 149(1), 113189. https://doi.org/10.1016/j.eswa.2020.113189
  • Szmerekovsky, J. G., & Venkateshan, P. (2012). An integer programming formulation for the project scheduling problem with irregular time–cost tradeoffs. Computers & Operations Research, 39(7), 1402–1410. https://doi.org/10.1016/j.cor.2011.08.011
  • Tavana, M., Abtahi, A. R., & Khalili-Damghani, K. (2014). A new multi-objective multi-mode model for solving preemptive time–cost–quality trade-off project scheduling problems. Expert Systems with Applications, 41(4), 1830–1846. https://doi.org/10.1016/j.eswa.2013.08.081
  • Tian, W., & Demeulemeester, E. (2014). Railway scheduling reduces the expected project makespan over roadrunner scheduling in a multi-mode project scheduling environment. Annals of Operations Research, 213(1), 271–291. https://doi.org/10.1007/s10479-012-1277-0
  • Van Den Eeckhout, M., Maenhout, B., & Vanhoucke, M. (2019). A heuristic procedure to solve the project staffing problem with discrete time/resource trade-offs and personnel scheduling constraints. Computers & Operations Research, 101(1), 144–161. https://doi.org/10.1016/j.cor.2018.09.008
  • Van de Vonder, S., Demeulemeester, E., Leus, R., & Herroelen, W. (2006). Proactive-reactive project scheduling trade-offs and procedures. In J. Józefowska & J. Weglarz (Eds.), Perspectives in modern project scheduling (pp. 25–51). Springer. https://doi.org/10.1007/978-0-387-33768-5_2
  • Vanhoucke, M., & Coelho, J. (2019). Resource-constrained project scheduling with activity splitting and setup times. Computers & Operations Research, 109(1), 230–249. https://doi.org/10.1016/j.cor.2019.05.004
  • Van Peteghem, V., & Vanhoucke, M. (2010). A genetic algorithm for the preemptive and non-preemptive multi-mode resource-constrained project scheduling problem. European Journal of Operational Research, 201(2), 409–418. https://doi.org/10.1016/j.ejor.2009.03.034
  • Van Peteghem, V., & Vanhoucke, M. (2014). An experimental investigation of metaheuristics for the multi-mode resource-constrained project scheduling problem on new dataset instances. European Journal of Operational Research, 235(1), 62–72. https://doi.org/10.1016/j.ejor.2013.10.012
  • Wang, H. W., Lin, J. R., & Zhang, J. P. (2020). Work package-based information modeling for resource-constrained scheduling of construction projects. Automation in Construction, 109(1), 102958. https://doi.org/10.1016/j.autcon.2019.102958
  • Wang, J., Hu, X., Demeulemeester, E., & Zhao, Y. (2019). A bi-objective robust resource allocation model for the RCPSP considering resource transfer costs. International Journal of Production Research, 59(2), 1–21. https://doi.org/10.1080/00207543.2019.1695168
  • Wang, W., Liu, X., & Qin, Y. (2018). A fuzzy fine-kinney-based risk evaluation approach with extended MULTIMOORA method based on Choquet integral. Computers & Industrial Engineering, 125(1), 111–123. https://doi.org/10.1016/j.cie.2018.08.019
  • Wolsey, L. A., & Nemhauser, G. L. (1999). Integer and combinatorial optimization (Vol. 55). John Wiley & Sons.
  • Xie, F., Li, H., & Xu, Z. (2021). Multi-mode resource-constrained project scheduling with uncertain activity cost. Expert Systems with Applications, 168(2), 114475. https://doi.org/10.1016/j.eswa.2020.114475
  • Yeganeh, F. T., & Zegordi, S. H. (2020). A multi-objective optimization approach to project scheduling with resiliency criteria under uncertain activity duration. Annals of Operations Research, 285(1), 161–196. https://doi.org/10.1007/s10479-019-03375-z
  • Yuan, Y., Ye, S., Lin, L., & Gen, M. (2021). Multi-objective multi-mode resource-constrained project scheduling with fuzzy activity durations in prefabricated building construction. Computers & Industrial Engineering, 158(1), 107316. https://doi.org/10.1016/j.cie.2021.107316
  • Zadeh, L. A. (1978). Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems, 1(1), 3–28. https://doi.org/10.1016/0165-0114(78)90029-5
  • Zapata, J. C., Hodge, B. M., & Reklaitis, G. V. (2008). The multimode resource constrained multiproject scheduling problem: Alternative formulations. AIChE Journal, 54(8), 2101–2119. https://doi.org/10.1002/aic.11522
  • Zheng, G., Zhu, N., Tian, Z., Chen, Y., & Sun, B. (2012). Application of a trapezoidal fuzzy AHP method for work safety evaluation and early warning rating of hot and humid environments. Safety Science, 50(2), 228–239. https://doi.org/10.1016/j.ssci.2011.08.042
  • Zhou, Y., Miao, J., Yan, B., & Zhang, Z. (2021). Stochastic resource-constrained project scheduling problem with time varying weather conditions and an improved estimation of distribution algorithm. Computers & Industrial Engineering, 157(1), 107322. https://doi.org/10.1016/j.cie.2021.107322

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.