A bi-objective robust resource allocation model for the RCPSP considering resource transfer costs

References

• Al-Fawzan, M. A., and M. Haouari. 2005. “A bi-Objective Model for Robust Resource-Constrained Project Scheduling.” International Journal of Production Economics 96 (2): 175–187. doi: 10.1016/j.ijpe.2004.04.002
   Web of Science ®Google Scholar
• Artigues, C., R. Leus, and F. T. Nobibon. 2013. “Robust Optimization for Resource-Constrained Project Scheduling with Uncertain Activity Durations.” Flexible Services & Manufacturing Journal 25 (1–2): 175–205. doi: 10.1007/s10696-012-9147-2
   Web of Science ®Google Scholar
• Artigues, C., P. Michelon, and S. Reusser. 2003. “Insertion Techniques for Static and Dynamic Resource-Constrained Project Scheduling.” European Journal of Operational Research 149 (2): 249–267. doi: 10.1016/S0377-2217(02)00758-0
   Web of Science ®Google Scholar
• Bérubé, J. F., M. Gendreau, and J. Y. Potvin. 2009. “An Exact -Constraint Method for bi-Objective Combinatorial Optimization Problems: Application to the Traveling Salesman Problem with Profits.” European Journal of Operational Research 194 (1): 39–50. doi: 10.1016/j.ejor.2007.12.014
   Web of Science ®Google Scholar
• Bie, L., N. Cui, and X. Zhang. 2012. “Buffer Sizing Approach with Dependence Assumption Between Activities in Critical Chain Scheduling.” International Journal of Production Research 50 (24): 7343–7356. doi: 10.1080/00207543.2011.649096
   Web of Science ®Google Scholar
• Bruni, M. E., L. D. P. Pugliese, P. Beraldi, and F. Guerriero. 2017. “An Adjustable Robust Optimization Model for the Resource-Constrained Project Scheduling Problem with Uncertain Activity Durations.” OMEGA 71: 66–84. doi: 10.1016/j.omega.2016.09.009
   Web of Science ®Google Scholar
• Chen, Z., E. Demeulemeester, S. Bai, and Y. Guo. 2018. “Efficient Priority Rules for the Stochastic Resource-Constrained Project Scheduling Problem.” European Journal of Operational Research 270 (3): 957–967. doi: 10.1016/j.ejor.2018.04.025
   Web of Science ®Google Scholar
• Chen, R., C. Liang, D. Gu, and Y. T. Leung. 2017. “A Multi-Objective Model for Multi-Project Scheduling and Multi-Skilled Staff Assignment for it Product Development Considering Competency Evolution.” International Journal of Production Research 55 (21): 6207–6234. doi: 10.1080/00207543.2017.1326641
   Web of Science ®Google Scholar
• Deb, K., A. Pratap, S. Agarwal, and T. Meyarivan. 2002. “A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II.” Transactions on Evolutionary Computation 6: 182–197. doi: 10.1109/4235.996017
   Web of Science ®Google Scholar
• Deblaere, F., E. Demeulemeester, W. Herroelen, and S. Van de Vonder. 2007. “Robust Resource Allocation Decisions in Resource-Constrained Projects.” Decision Sciences 38 (1): 5–37. doi: 10.1111/j.1540-5915.2007.00147.x
   Web of Science ®Google Scholar
• Delgoshaei, A., M. K. Ariffin, and B. T. Baharudin. 2016. “Pre-emptive Resource-Constrained Multimode Project Scheduling Using Genetic Algorithm: A Dynamic Forward Approach.” Journal of Industrial Engineering and Management 9 (3): 732–785. doi: 10.3926/jiem.1522
   Google Scholar
• Delgoshaei, A., M. K. Ariffin, B. T. Baharudin, and Z. Leman. 2015. “Minimizing Makespan of a Resource-Constrained Scheduling Problem: A Hybrid Greedy and Genetic Algorithms.” International Journal of Industrial Engineering Computations 6 (4): 503–520. doi: 10.5267/j.ijiec.2015.5.002
   Google Scholar
• Delgoshaei, A., T. Rabczuk, A. Ali, and M. K. Ariffin. 2017. “An Applicable Method for Modifying Over-Allocated Multi-Mode Resource Constraint Schedules in the Presence of Preemptive Resources.” Annals of Operations Research 259 (1–2): 85–117. doi: 10.1007/s10479-016-2336-8
   Web of Science ®Google Scholar
• Demeulemeester, E., and W. Herroelen. 1992. “A Branch-and-Bound Procedure for the Multiple Resource-Constrained Project Scheduling Problem.” Management Science 38 (12): 1803–1818. doi: 10.1287/mnsc.38.12.1803
   Web of Science ®Google Scholar
• Demeulemeester, E., and W. Herroelen. 2011. Robust Project Scheduling. Hanover, USA: Now Publishers Inc.
   Google Scholar
• Hu, X., N. Cui, and E. Demeulemeester. 2015. “Effective Expediting to Improve Project due Date and Cost Performance Through Buffer Management.” International Journal of Production Research 53 (5): 1460–1471. doi: 10.1080/00207543.2014.948972
   Web of Science ®Google Scholar
• Hu, X., E. Demeulemeester, N. Cui, J. Wang, and W. Tian. 2017. “Improved Critical Chain Buffer Management Framework Considering Resource Costs and Schedule Stability.” Flexible Services & Manufacturing Journal 29 (2): 159–183. doi: 10.1007/s10696-016-9241-y
   Web of Science ®Google Scholar
• Hu, X., J. Wang, and K. Leng. 2019. “The Interaction Between Critical Chain Sequencing, Buffer Sizing and Reactive Actions in a CC/BM Framework.” Asia-Pacific Journal of Operational Research 36 (3): 1950010. doi: 10.1142/S0217595919500106
   Web of Science ®Google Scholar
• Kadri, R. L., and F. F. Boctor. 2018. “An Efficient Genetic Algorithm to Solve the Resource-Constrained Project Scheduling Problem with Transfer Times: the Single Mode Case.” European Journal of Operational Research 265: 454–462. doi: 10.1016/j.ejor.2017.07.027
   Web of Science ®Google Scholar
• Kolisch, R., and A. Sprecher. 1997. “PSPLIB – a Project Scheduling Problem Library.” European Journal of Operational Research 96 (1): 205–216. doi: 10.1016/S0377-2217(96)00170-1
   Web of Science ®Google Scholar
• Krüger, D., and A. Scholl. 2009. “A Heuristic Solution Framework for the Resource Constrained (Multi-)Project Scheduling Problem with Sequence-Dependent Transfer Times.” European Journal of Operational Research 197 (2): 492–508. doi: 10.1016/j.ejor.2008.07.036
   Web of Science ®Google Scholar
• Krüger, D., and A. Scholl. 2010. “Managing and Modelling General Resource Transfers in (Multi-)Project Scheduling.” OR Spectrum 32 (2): 369–394. doi: 10.1007/s00291-008-0144-5
   Web of Science ®Google Scholar
• Lamas, P., and E. Demeulemeester. 2016. “A Purely Proactive Scheduling Procedure for the Resource-Constrained Project Scheduling Problem with Stochastic Activity Durations.” Journal of Scheduling 19 (4): 409–428. doi: 10.1007/s10951-015-0423-3
   Web of Science ®Google Scholar
• Lambrechts, O., E. Demeulemeester, and W. Herroelen. 2011. “Time Slack-Based Techniques for Robust Project Scheduling Subject to Resource Uncertainty.” Annals of Operations Research 186 (1): 443–464. doi: 10.1007/s10479-010-0777-z
   Web of Science ®Google Scholar
• Leus, R., and W. Herroelen. 2004. “Stability and Resource Allocation in Project Planning.” IIE Transactions 36: 1–16. doi: 10.1080/07408170490447348
   Web of Science ®Google Scholar
• Li, H., L. Xiong, Y. Liu, and H. Li. 2018. “An Effective Genetic Algorithm for the Resource Levelling Problem with Generalised Precedence Relations.” International Journal of Production Research 56 (5): 2054–2075. doi: 10.1080/00207543.2017.1355120
   Web of Science ®Google Scholar
• Li, H., and Q. Zhang. 2009. “Multiobjective Optimization Problems with Complicated Pareto Sets, MOEA/D and NSGA-II.” IEEE Transactions on Evolutionary Computation 13 (2): 284–302. doi: 10.1109/TEVC.2008.925798
   Web of Science ®Google Scholar
• Liang, Y., N. Cui, X. Hu, and E. Demeulemeester. 2019. “The Integration of Resource Allocation and Time Buffering for bi-Objective Robust Project Scheduling.” International Journal of Production Research. doi:10.1080/00207543.2019.1636319.
   PubMed Web of Science ®Google Scholar
• Liu, J., and M. Lu. 2019. “Robust Dual-Level Optimization Framework for Resource-Constrained Multiproject Scheduling for a Prefabrication Facility in Construction.” Journal of Computing in Civil Engineering 33 (2): 04018067. doi: 10.1061/(ASCE)CP.1943-5487.0000816
   Web of Science ®Google Scholar
• Lu, Z., and X. Liu. 2018. “Algorithm for Resource-Constrained Project Scheduling Problem with Resource Transfer Time.” Acta Automatica Sinica 44 (6): 1028–1036. doi: 10.1007/s10114-017-7354-1
   Google Scholar
• Policella, N. 2005. “Scheduling with Uncertainty: A Proactive Approach Using Partial Order Schedules.” AI Communications 18 (2): 165–167.
   Web of Science ®Google Scholar
• Poppenborg, J., and S. Knust. 2016. “A Flow-Based Tabu Search Algorithm for the RCPSP with Transfer Times.” OR Spectrum 38 (2): 305–334. doi: 10.1007/s00291-015-0402-2
   Web of Science ®Google Scholar
• Rabiee, M., M. Zandieh, and P. Ramezani. 2012. “Bi-objective Partial Flexible job Shop Scheduling Problem: NSGA-II, NRGA, MOGA and PAES Approaches.” International Journal of Production Research 50 (24): 7327–7342. doi: 10.1080/00207543.2011.648280
   Web of Science ®Google Scholar
• Rostami, S., S. Creemers, and R. Leus. 2018. “New Strategies for Stochastic Resource-Constrained Project Scheduling.” Journal of Scheduling 21 (3): 349–365. doi: 10.1007/s10951-016-0505-x
   Web of Science ®Google Scholar
• Suman, B., and P. Kumar. 2006. “A Survey of Simulated Annealing as a Tool for Single and Multiobjective Optimization.” Journal of the Operational Research Society 57 (10): 1143–1160. doi: 10.1057/palgrave.jors.2602068
   Web of Science ®Google Scholar
• Tabrizi, B. H., and S. F. Ghaderi. 2016. “A Robust bi-Objective Model for Concurrent Planning of Project Scheduling and Material Procurement.” Computers & Industrial Engineering 98: 11–29. doi: 10.1016/j.cie.2016.05.017
   Web of Science ®Google Scholar
• Tian, W., and E. Demeulemeester. 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. doi: 10.1007/s10479-012-1277-0
   Web of Science ®Google Scholar
• Van de Vonder, S., E. Demeulemeester, and W. Herroelen. 2008. “Proactive Heuristic Procedures for Robust Project Scheduling: An Experimental Analysis.” European Journal of Operation Research 189 (3): 723–733. doi: 10.1016/j.ejor.2006.10.061
   Web of Science ®Google Scholar
• Vega-Velázquez, MÁ, A. García-Nájera, and H. Cervantes. 2018. “A Survey on the Software Project Scheduling Problem.” International Journal of Production Economics 202: 145–161. doi: 10.1016/j.ijpe.2018.04.020
   Web of Science ®Google Scholar
• Wang, Y., Z. He, L. P. Kerkhove, and M. Vanhoucke. 2017. “On the Performance of Priority Rules for the Stochastic Resource Constrained Multi-Project Scheduling Problem.” Computers & Industrial Engineering 114: 223–234. doi: 10.1016/j.cie.2017.10.021
   Web of Science ®Google Scholar
• Wang, L., and X. Zheng. 2018. “A Knowledge-Guided Multi-Objective Fruit fly Optimization Algorithm for the Multi-Skill Resource Constrained Project Scheduling Problem.” Swarm and Evolutionary Computation 38: 54–63. doi: 10.1016/j.swevo.2017.06.001
   Web of Science ®Google Scholar
• Yen, G. G., and Z. He. 2014. “Performance Metric Ensemble for Multiobjective Evolutionary Algorithms.” IEEE Transactions on Evolutionary Computation 18 (1): 131–144. doi: 10.1109/TEVC.2013.2240687
   Web of Science ®Google Scholar
• Zhang, J., X. Song, and E. Díaz. 2016. “Project Buffer Sizing of a Critical Chain Based on Comprehensive Resource Tightness.” European Journal of Operational Research 248 (1): 174–182. doi: 10.1016/j.ejor.2015.07.009
   Web of Science ®Google Scholar
• Zhang, J., X. Song, and E. Díaz. 2017. “Critical Chain Project Buffer Sizing Based on Resource Constraints.” International Journal of Production Research 55 (3): 671–683. doi: 10.1080/00207543.2016.1200151
   Web of Science ®Google Scholar
• Zheng, W., Z. He, N. Wang, and T. Jia. 2018. “Proactive and Reactive Resource-Constrained max-npv Project Scheduling with Random Activity Duration.” Journal of the Operational Research Society 69 (1): 115–126. doi: 10.1057/s41274-017-0198-3
   Web of Science ®Google Scholar
• Zoraghi, N., A. Shahsavar, and S. T. A. Niaki. 2017. “A Hybrid Project Scheduling and Material Ordering Problem: Modeling and Solution Algorithms.” Applied Soft Computing 58 (C): 700–713. doi: 10.1016/j.asoc.2017.05.030
   Web of Science ®Google Scholar