April  2016, 12(2): 565-593. doi: 10.3934/jimo.2016.12.565

Bi-level multiple mode resource-constrained project scheduling problems under hybrid uncertainty

1. 

School Economics & Management, Nanjing University of Science and Technology, Nanjing 210094, China

2. 

State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu 610064

Received  June 2014 Revised  February 2015 Published  June 2015

This study focuses on the multi-mode resource-constrained projects scheduling problem (MRCPSP), which considers the complex hierarchical organization structure and hybrid uncertainty environment in the decision making process. A bi-level multi-objective MRCPSP model with fuzzy random coefficients and bi-random coefficients is developed for the MRCPSP. In the model, construction contractor, the upper level decision maker (ULDM), aims to minimize the consumption of resources and maximize the quality level of project. Meanwhile, outsourcing partner, the lower level decision maker (LLDM), tries to schedule the activities under resource allocation with the objective of minimizing the total tardiness penalty cost. To deal with the uncertainty variables, the fuzzy random parameters are transformed into the trapezoidal fuzzy variables, which are de-fuzzified by the expected value subsequently. For the bi-random parameters, the expected value operator is employed. After obtaining the equivalent crisp model, the passive congregation-based bi-level multiple objective particle swarm optimization algorithm (PC-based BL-MOPSO) is designed to obtain the Pareto solutions. Finally, a practical application is presented to verify the practicability of the proposed bi-level multi-objective MRCPSP model and the efficiency of algorithm.
Citation: Zhe Zhang, Jiuping Xu. Bi-level multiple mode resource-constrained project scheduling problems under hybrid uncertainty. Journal of Industrial & Management Optimization, 2016, 12 (2) : 565-593. doi: 10.3934/jimo.2016.12.565
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show all references

References:
[1]

China Water, URL:, , ().   Google Scholar

[2]

Xiluodu, Chinese National Committee on Large Dams,, URL: , ().   Google Scholar

[3]

Information Sciences, 178 (2008), 468-484. doi: 10.1016/j.ins.2007.03.029.  Google Scholar

[4]

International Journal of Intelligent Systems, 27 (2012), 873-907. doi: 10.1002/int.21552.  Google Scholar

[5]

European Journal of Operational Research, 161 (2005), 86-110. doi: 10.1016/j.ejor.2003.08.027.  Google Scholar

[6]

Computers and Industrial Engineering, 56 (2009), 411-416. doi: 10.1016/j.cie.2008.07.001.  Google Scholar

[7]

European Journal of Operational Research, 208 (2011), 57-66. doi: 10.1016/j.ejor.2010.07.021.  Google Scholar

[8]

Master Thesis, University of Gävle, 2009. Google Scholar

[9]

International Journal of Computational Science and Engineering, 6 (2011), 5-15. Google Scholar

[10]

Computers and Chemical Engineering, 28 (2004), 1039-1058. Google Scholar

[11]

European Journal of Operational Research, 214 (2011), 308-316. doi: 10.1016/j.ejor.2011.04.019.  Google Scholar

[12]

New York: Wiley, 1977. Google Scholar

[13]

IRE Transactions on Engineering Management, 7 (1960), 103-107. doi: 10.1109/IRET-EM.1960.5007550.  Google Scholar

[14]

Journal of Management in Engineering, Inpress, (2013). Google Scholar

[15]

Journal of Global Optimization, 51 (2011), 245-254. doi: 10.1007/s10898-010-9595-8.  Google Scholar

[16]

BioSystems, 78 (2004), 135-147. doi: 10.1016/j.biosystems.2004.08.003.  Google Scholar

[17]

European Journal of Operational Research, 165 (2005), 289-306. doi: 10.1016/j.ejor.2004.04.002.  Google Scholar

[18]

Applied Mathematics and Computation, 168 (2005), 342-353. doi: 10.1016/j.amc.2004.09.002.  Google Scholar

[19]

IIE Transactions, 42 (2009), 16-30. doi: 10.1080/07408170902942683.  Google Scholar

[20]

In Proceedings of the IEEE Conference on Neural Networks, Piscataway: IEEE Service Center, 1995, 1942-1948. doi: 10.1109/ICNN.1995.488968.  Google Scholar

[21]

Computers and Operations Research, 37 (2010), 2131-2140. doi: 10.1016/j.cor.2010.03.002.  Google Scholar

[22]

Constraints, 16 (2011), 317-340. doi: 10.1007/s10601-010-9102-3.  Google Scholar

[23]

Computer Aided Chemical Engineering, 1627 (2009), 681-686. doi: 10.1016/S1570-7946(09)70334-7.  Google Scholar

[24]

Computers and Mathematics with Applications, 58 (2009), 678-685. doi: 10.1016/j.camwa.2009.02.028.  Google Scholar

[25]

Information Sciences, 15 (1978), 1-29. doi: 10.1016/0020-0255(78)90019-1.  Google Scholar

[26]

Journal of Scheduling, 11 (2008), 369-385. doi: 10.1007/s10951-007-0021-0.  Google Scholar

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International Journal of Production Economics, 111 (2008), 493-508. doi: 10.1016/j.ijpe.2007.02.003.  Google Scholar

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[29]

IEEE Transactions on Fuzzy Systems, 10 (2002), 445-450. Google Scholar

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China Three Gorges Copporation, (2012). Google Scholar

[31]

Journal of Uncertain Systems, 4 (2010), 123-132. Google Scholar

[32]

Journal of Tongji University (Natural Science), 38 (2010), 380-385. Google Scholar

[33]

Computers and Industrial Engineering, 53 (2007), 433-453. doi: 10.1016/j.cie.2004.11.003.  Google Scholar

[34]

Fuzzy Sets and Systems, 2 (1979), 153-165. doi: 10.1016/0165-0114(79)90022-8.  Google Scholar

[35]

Journal of Mathematical Analysis and Applications, 114 (1986), 409-422. doi: 10.1016/0022-247X(86)90093-4.  Google Scholar

[36]

In Proc. IEEE Int. Conf. on Neural Networks, 1998, pp. 69-73. Google Scholar

[37]

China Three Gorges Construction, 11 (2004), 34-37. Google Scholar

[38]

International Journal of Production Economics, 131 (2011), 709-720. doi: 10.1016/j.ijpe.2011.02.020.  Google Scholar

[39]

Transportation Planning and Technology, 36 (2013), 352-376. doi: 10.1080/03081060.2013.798486.  Google Scholar

[40]

Engineering Optimization, Inpress, (2012). doi: 10.1080/0305215X.2012.709514.  Google Scholar

[41]

Journal of Scheduling, 15 (2012), 253-272. doi: 10.1007/s10951-010-0173-1.  Google Scholar

[42]

Information Sciences, 179 (2009), 2997-3017. doi: 10.1016/j.ins.2009.04.009.  Google Scholar

[43]

Modern Applied Science, 3 (2009), 161-165. Google Scholar

[44]

Computer-Aided Civil and Infrastructure Engineering, 21 (2006), 93-103. Google Scholar

[45]

Journal of Applied Mathematics, 21 (2012), Article ID 626717, 13 pages. doi: 10.1155/2012/626717.  Google Scholar

[46]

Doctoral Dissertation, Sichuan University (In Chinese), 2011. Google Scholar

[47]

International Journal of Civil Engineering, 11 (2013), 1-13. Google Scholar

[48]

INFORMS Journal on Computing, 18 (2006), 377-390. doi: 10.1287/ijoc.1040.0121.  Google Scholar

[49]

Journal of Scheduling, 10 (2007), 167-180. doi: 10.1007/s10951-007-0008-x.  Google Scholar

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