IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v173y2021ics0040162521005709.html
   My bibliography  Save this article

A new approach for material ordering and multi-mode resource constraint project scheduling problem in a multi-site context under interval-valued fuzzy uncertainty

Author

Listed:
  • Patoghi, Amirhosein
  • Mousavi, Seyed Meysam

Abstract

Taking both material procurement and project scheduling problem simultaneously has been proved the most noteworthy areas in project management. The ordering amount is a key factor due to the fact that through keeping a full stock of required materials, the probability of material shortage and corresponding inefficiency decline but the costs of inventory holding increase significantly. Besides, the delay in individual activities and consequently in project completion increase if a small amount of needed material is purchased. The multi-site context as one of the new resource constraint project scheduling problem (RCPSP) extensions has been widely utilized in some applications in real-world cases, especially in construction projects. In this paper, a new mathematical model is proposed for the combination of ordering problems considering all-unit discount policy and multi-mode RCPSP (MRCPSP) in the multi-site context. The developed model aims to minimize the project total cost as well as the completion time of the project. In the novel proposed mathematical model, the transportation time is crucial and depends on the site that activities are assigned. With respect to the inherent uncertainties in project management, the duration of activities, transportation time between sites, and lead time are regarded as triangular interval-valued fuzzy numbers. In addition, a new hybrid multi-objective uncertainty approach is presented to handle interval-valued fuzzy mathematical model. The results obtained by solving the presented model employing an application example from MPSPLIB data set and a real case study about seawater intake systems are appraised considering key parameters to validate the proposed model and provide some managerial insights.

Suggested Citation

  • Patoghi, Amirhosein & Mousavi, Seyed Meysam, 2021. "A new approach for material ordering and multi-mode resource constraint project scheduling problem in a multi-site context under interval-valued fuzzy uncertainty," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
  • Handle: RePEc:eee:tefoso:v:173:y:2021:i:c:s0040162521005709
    DOI: 10.1016/j.techfore.2021.121137
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162521005709
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.techfore.2021.121137?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Dodin, B. & Elimam, A.A., 2008. "Integration of equipment planning and project scheduling," European Journal of Operational Research, Elsevier, vol. 184(3), pages 962-980, February.
    2. R. E. Bellman & L. A. Zadeh, 1970. "Decision-Making in a Fuzzy Environment," Management Science, INFORMS, vol. 17(4), pages 141-164, December.
    3. De Reyck, Bert & Herroelen, Willy, 1999. "The multi-mode resource-constrained project scheduling problem with generalized precedence relations," European Journal of Operational Research, Elsevier, vol. 119(2), pages 538-556, December.
    4. Kai Watermeyer & Jürgen Zimmermann, 2020. "A branch-and-bound procedure for the resource-constrained project scheduling problem with partially renewable resources and general temporal constraints," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(2), pages 427-460, June.
    5. Pérez, Fátima & Gómez, Trinidad & Caballero, Rafael & Liern, Vicente, 2018. "Project portfolio selection and planning with fuzzy constraints," Technological Forecasting and Social Change, Elsevier, vol. 131(C), pages 117-129.
    6. Kadri, Roubila Lilia & Boctor, Fayez F., 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, Elsevier, vol. 265(2), pages 454-462.
    7. Arenas Parra, M. & Bilbao Terol, A. & Perez Gladish, B. & Rodriguez Uria, M. V., 2005. "Solving a multiobjective possibilistic problem through compromise programming," European Journal of Operational Research, Elsevier, vol. 164(3), pages 748-759, August.
    8. Petrovic, Dobrila, 2001. "Simulation of supply chain behaviour and performance in an uncertain environment," International Journal of Production Economics, Elsevier, vol. 71(1-3), pages 429-438, May.
    9. Messelis, Tommy & De Causmaecker, Patrick, 2014. "An automatic algorithm selection approach for the multi-mode resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 233(3), pages 511-528.
    10. Bajis Dodin, 2006. "A Practical and Accurate Alternative to PERT," International Series in Operations Research & Management Science, in: Joanna Józefowska & Jan Weglarz (ed.), Perspectives in Modern Project Scheduling, chapter 0, pages 3-23, Springer.
    11. Jimenez, Mariano & Arenas, Mar & Bilbao, Amelia & Rodri'guez, M. Victoria, 2007. "Linear programming with fuzzy parameters: An interactive method resolution," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1599-1609, March.
    12. Aria Shahsavar & Nima Zoraghi & Babak Abbasi, 2018. "Integration of resource investment problem with quantity discount problem in material ordering for minimizing resource costs of projects," Operational Research, Springer, vol. 18(2), pages 315-342, July.
    13. Saurav Datta & Chitrasen Samantra & Siba Sankar Mahapatra & Sabyasachi Banerjee & Asish Bandyopadhyay, 2012. "Green supplier evaluation and selection using VIKOR method embedded in fuzzy expert system with interval-valued fuzzy numbers," International Journal of Procurement Management, Inderscience Enterprises Ltd, vol. 5(5), pages 647-678.
    14. Calabrese, Armando & Costa, Roberta & Levialdi, Nathan & Menichini, Tamara, 2019. "Integrating sustainability into strategic decision-making: A fuzzy AHP method for the selection of relevant sustainability issues," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 155-168.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xumai Qi & Dongdong Zhang & Hu Lu & Rupeng Li, 2023. "A GA-Based Scheduling Method for Civil Aircraft Distributed Production with Material Inventory Replenishment Consideration," Mathematics, MDPI, vol. 11(14), pages 1-25, July.
    2. Renu, & Upadhyay, Ranjit Kumar & Tiwari, S.P. & Yadav, R.P., 2023. "Analysis of interval-valued model for interaction between plankton-fish population in marine ecosystem," Ecological Modelling, Elsevier, vol. 484(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hartmann, Sönke & Briskorn, Dirk, 2022. "An updated survey of variants and extensions of the resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 297(1), pages 1-14.
    2. Peidro, David & Mula, Josefa & Jiménez, Mariano & del Mar Botella, Ma, 2010. "A fuzzy linear programming based approach for tactical supply chain planning in an uncertainty environment," European Journal of Operational Research, Elsevier, vol. 205(1), pages 65-80, August.
    3. Babazadeh, Reza & Razmi, Jafar & Pishvaee, Mir Saman & Rabbani, Masoud, 2017. "A sustainable second-generation biodiesel supply chain network design problem under risk," Omega, Elsevier, vol. 66(PB), pages 258-277.
    4. H. Zhang & C. M. Tam, 2003. "Fuzzy decision-making for dynamic resource allocation," Construction Management and Economics, Taylor & Francis Journals, vol. 21(1), pages 31-41.
    5. Figueroa–García, Juan Carlos & Hernández, Germán & Franco, Carlos, 2022. "A review on history, trends and perspectives of fuzzy linear programming," Operations Research Perspectives, Elsevier, vol. 9(C).
    6. Niu, G. & Li, Y.P. & Huang, G.H. & Liu, J. & Fan, Y.R., 2016. "Crop planning and water resource allocation for sustainable development of an irrigation region in China under multiple uncertainties," Agricultural Water Management, Elsevier, vol. 166(C), pages 53-69.
    7. Kargar, Bahareh & Pishvaee, Mir Saman & Jahani, Hamed & Sheu, Jiuh-Biing, 2020. "Organ transportation and allocation problem under medical uncertainty: A real case study of liver transplantation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 134(C).
    8. Tosarkani, Babak Mohamadpour & Amin, Saman Hassanzadeh & Zolfagharinia, Hossein, 2020. "A scenario-based robust possibilistic model for a multi-objective electronic reverse logistics network," International Journal of Production Economics, Elsevier, vol. 224(C).
    9. Jian-Jun Wang & Zongli Dai & Ai-Chih Chang & Jim Junmin Shi, 2022. "Surgical scheduling by Fuzzy model considering inpatient beds shortage under uncertain surgery durations," Annals of Operations Research, Springer, vol. 315(1), pages 463-505, August.
    10. Shih-Pin Chen, 2017. "Effects of fuzzy data on decision making in a competitive supply chain," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(10), pages 1146-1160, October.
    11. Tubagus Robbi Megantara & Sudradjat Supian & Diah Chaerani, 2022. "Strategies to Reduce Ride-Hailing Fuel Consumption Caused by Pick-Up Trips: A Mathematical Model under Uncertainty," Sustainability, MDPI, vol. 14(17), pages 1-18, August.
    12. Kajal Chatterjee & Samarjit Kar, 2016. "Multi-criteria analysis of supply chain risk management using interval valued fuzzy TOPSIS," OPSEARCH, Springer;Operational Research Society of India, vol. 53(3), pages 474-499, September.
    13. Tang, Christopher S. & Davarzani, Hoda & Sarkis, Joseph, 2015. "Quantitative models for managing supply chain risks: A reviewAuthor-Name: Fahimnia, Behnam," European Journal of Operational Research, Elsevier, vol. 247(1), pages 1-15.
    14. Zhang, Y.M. & Lu, H.W. & Nie, X.H. & He, L. & Du, P., 2014. "An interactive inexact fuzzy bounded programming approach for agricultural water quality management," Agricultural Water Management, Elsevier, vol. 133(C), pages 104-111.
    15. S. Wang & G. Huang, 2012. "Identifying Optimal Water Resources Allocation Strategies through an Interactive Multi-Stage Stochastic Fuzzy Programming Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(7), pages 2015-2038, May.
    16. Niakan, Farzad & Rahimi, Mohammad, 2015. "A multi-objective healthcare inventory routing problem; a fuzzy possibilistic approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 80(C), pages 74-94.
    17. Mula, Josefa & Peidro, David & Poler, Raul, 2010. "The effectiveness of a fuzzy mathematical programming approach for supply chain production planning with fuzzy demand," International Journal of Production Economics, Elsevier, vol. 128(1), pages 136-143, November.
    18. Bitar, Sandro D.B. & da Costa Junior, Carlos T. & Barreiros, José A.L. & Neto, João C. do L., 2009. "Expansion of isolated electrical systems in the Amazon: An approach using fuzzy multi-objective mathematical programming," Energy Policy, Elsevier, vol. 37(10), pages 3899-3905, October.
    19. Piao, M.J. & Li, Y.P. & Huang, G.H. & Nie, S., 2015. "Risk analysis for Shanghai's electric power system under multiple uncertainties," Energy, Elsevier, vol. 87(C), pages 104-119.
    20. Mula, J. & Poler, R. & Garcia-Sabater, J.P. & Lario, F.C., 2006. "Models for production planning under uncertainty: A review," International Journal of Production Economics, Elsevier, vol. 103(1), pages 271-285, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:tefoso:v:173:y:2021:i:c:s0040162521005709. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.