Skip to main content
SpringerLink
Log in

Simulation Modeling and Analysis for Sustainable Supply Chains

  • Chapter
  • First Online:
Sustainable Logistics and Production in Industry 4.0

Part of the book series: EcoProduction ((ECOPROD))

  • 1493 Accesses

Abstract

In their decision-making supply chain management, specialists are usually focused on some characteristic performance metrics that mainly influence the construction of their decision support models and partly also the results. Many of the supply chain issues affect the sustainability performance of companies. Since supply chains are complex adaptive systems, appropriate modeling methods are required to tackle their inherent complexity and lead to desired results that contribute to the achievement of sustainable objectives. From the viewpoint of system theory, they should enable the monitoring, analysis, and control of supply chains providing opportunities for system-wide integration. Since multiple views and layers of a supply chain or multiple interconnected supply chains must be considered, different modeling and analysis techniques are used to achieve the desired levels of detail. In this chapter, three simulation modeling and analysis methods are assessed, considering their suitability to support decision-making in diverse supply chain management problems and scenarios. These results are joined in guidelines for the construction of coherent and consistent simulation models that would enable multilayered and multifaceted analysis of common supply chain management problems and lead to making decisions that efficiently utilize supply chain resources, shorten lead times, and eliminate unnecessary waste.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 139.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 179.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 179.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Angerhofer BJ, Angelides MC (2000) System dynamics modelling in supply chain management: research review. In: Proceedings of the 32nd conference on winter simulation, society for computer simulation international, San Diego, CA, USA, pp 342–351

    Google Scholar 

  • Behdani B (2012) Evaluation of paradigms for modeling supply chains as complex socio-technical systems. In: Proceedings of the winter simulation conference, winter simulation conference, December 2012, p 413

    Google Scholar 

  • Behdani B, van Dam KH, Lukszo Z (2013) Agent-based models of supply chains. In: van Dam K, Nikolic I, Lukszo Z (eds) Agent-based modelling of socio-technical systems, vol 9. Agent-based social systems. Springer, Netherlands, Dordrecht, pp 151–180

    Chapter  Google Scholar 

  • Bowersox DJ, Closs DJ, Cooper MB, Bowersox JC (2013) Supply chain logistics management. McGraw-Hill/Irwin, New York

    Google Scholar 

  • Carter CR, Rogers DS (2008) A framework of sustainable supply chain management: moving toward new theory. Int J Phys Distrib Logis Manag 38(5):360–387

    Article  Google Scholar 

  • Chopra S, Meindl P (2007) Supply chain management: strategy, planning and operation. Pearson Prentice Hall, New Jersey

    Google Scholar 

  • Christopher M (2011) Logistics and supply chain management: creating value-adding networks. FT Press, London

    Google Scholar 

  • Conant RC, Ashby WR (1970) Every good regulator of a system must be a model of that system. Int J Syst Sci 1(2):89–97

    Article  MathSciNet  MATH  Google Scholar 

  • Coyle J, Bardi E, Langley J (2003) The management of business logistics: a supply chain perspective. South-Western Thomson Learning, Mason, OH

    Google Scholar 

  • Georgiadis P, Vlachos D, Iakovou E (2005) A system dynamics modeling framework for the strategic supply chain management of food chains. J Food Eng 70(3):351–364

    Article  Google Scholar 

  • Gómez-Cruz NA, Loaiza Saa I, Ortega Hurtado FF (2017) Agent-based simulation in management and organizational studies: a survey. Eur J Manag Bus Econ 26(3):313–328

    Article  Google Scholar 

  • Grzybowska K (2012) Sustainability in the supply chain: analysing the enablers. In: Golinska P, Romano C (eds) Environmental issues in supply chain management. EcoProduction (environmental issues in logistics and manufacturing). Springer, Berlin

    Chapter  Google Scholar 

  • Grzybowska K, Hoffa-Dabrowska P (2018) Durability of supply chains as non-renewable systems. In: Intelligent systems in production engineering and maintenance (ISPEM 2017), vol 637, pp 227–237

    Google Scholar 

  • Grzybowska K, Awasthi A, Hussain M (2014) Modeling enablers for sustainable logistics collaboration integrating—Canadian and Polish perspectives. In: 2014 federated conference on computer science and information systems, pp 1311–1319, Warsaw

    Google Scholar 

  • Gumzej R, Rosi B (2017a) An agent-based simulation of a Qos-oriented supply chain. Promet Traffic Transp 29(6):647–655

    Article  Google Scholar 

  • Gumzej R, Rosi B (2017b) An SD-based DST for solving a volumes problem. In: SOR’17 proceedings international symposium on operational research in Slovenia, Bled, 27–29 September 2017, pp 129–134

    Google Scholar 

  • Harland C, Lamming R, Cousins P (1999) Developing the concept of supply strategy. Int J Oper Prod Manag 19(7):650–673

    Article  Google Scholar 

  • Harrison TP (2005) Principles for the strategic design of supply chains. In: Harrison TP, Lee HL, Neale JJ (eds) The practice of supply chain management. Springer, New York, pp 3–12

    Google Scholar 

  • Holland JH (1995) Hidden order: how adaptation builds complexity. Addison Wesley Longman Publishing Co. Inc., Redwood City, CA, USA

    Google Scholar 

  • Ip WH, Chan SL, Lam CY (2011) Modeling supply chain performance and stability. Ind Manag Data Syst 111(8):1332–1354

    Article  Google Scholar 

  • King DH, Harrison HS (2013) “JaamSim” open-source simulation software. In: Proceedings of the 2013 grand challenges on modeling and simulation conference (GCMS’13), Society for modeling & simulation international, Article no 1, p 6, Vista, CA

    Google Scholar 

  • Kleijnen JPC (2005) Supply chain simulation tools and techniques: a survey. Int J Simul Process Model 1(1–2):82–89

    Article  Google Scholar 

  • Kumar NR (2014) Optimisation of supply chain network modeling and performance measurement in flow of production. J Supply Chain Manag Syst 3(4):1–6

    Google Scholar 

  • Mentzer J, DeWitt W, Keebler J, Min S, Nix N, Smith C, Zacharia Z (2001) Defining supply chain management. J Bus Logis 22(2):1–25

    Article  Google Scholar 

  • North M, Macal C, Aubin J, Thimmapuram P, Bragen M, Hahn J, Karr J, Brigham N, Lacy ME, Hampton D (2010) Multiscale agent-based consumer market modeling. Complexity 15(5):37–47

    Google Scholar 

  • Pereira JV (2009) SD-DES model: a new approach for implementing an e-supply chain. J Model Manag 4(2):134–148

    Article  Google Scholar 

  • Pero M, Abdelkafi N, Sianesi A, Blecker T (2010) A framework for the alignment of new product development and supply chains. Supply Chain Manag: Int J 15(2):115–128

    Article  Google Scholar 

  • Ramos TRP, Gomes MI, Barbosa-Póvoa AP (2014) Planning a sustainable reverse logistics system: balancing costs with environmental and social concerns. Omega 48(C):60–74 (2014)

    Article  Google Scholar 

  • Rashid S, Weston R (2012) Design of an integrated methodology for analytical design of complex supply chains. Adv Decis Sci, Article ID 589254 (2012)

    Google Scholar 

  • Rosi B, Mulej M (2006) The dialectical network thinking—a new systems theory concerned with management. Kybernetes 35(7/8):1165–1178

    Article  MATH  Google Scholar 

  • Samaranayake P, Laosirihongthong T (2016) Configuration of supply chain integration and delivery performance. Unitary structure model and fuzzy approach. J Model Manag 11(1):43–74

    Article  Google Scholar 

  • Shah N (2005) Process industry supply chains: advances and challenges. Comput Chem Eng 29(6):1225–1235

    Article  Google Scholar 

  • Shi VG, Koh SCL, Baldwin J, Cucchiella F (2012) Natural resource based green supply chain management. Supply Chain Manag: Int J 17(1):54–67

    Article  Google Scholar 

  • Singh RJ, Sohani N, Marmat H (2013) Effect of lean/JIT practices and supply chain integration on lead time performance. J Supply Chain Manag Syst 2(2):37–41

    Google Scholar 

  • Stank T, Keller S, Daugherty P (2001) Supply chain collaboration and logistical service performance. J Bus Logist 22(1):29–48

    Article  Google Scholar 

  • Strandhagen JO, Vallandingham LR, Fragapane G, Strandhagen JW, Stangeland ABH, Sharma N (2017) Logistics 4.0 and emerging sustainable business models. Adv Manuf 5(4):359–369

    Article  Google Scholar 

  • Tako AA, Robinson S (2012) The application of discrete event simulation and system dynamics in the logistics and supply chain context. Decis Support Syst 52(4):802–815

    Article  Google Scholar 

  • Wang C-N, Ho H-XT, Luo S-H, Lin T-F (2017) An integrated approach to evaluating and selecting green logistics providers for sustainable development. Sustainability 9(2):218 (2017)

    Article  Google Scholar 

  • Xia W, Sun J (2013) Simulation guided value stream mapping and lean improvement: a case study of a tubular machining facility. J Ind Eng Manag 6(2):456–476

    Google Scholar 

  • Yoho KD, Rappold JA (2011) Beyond lean: production and inventory policy for the old economy. Prod Inven Manag J 47(2):56–68

    Google Scholar 

  • Zhang G, Shang J, Li W (2011) Collaborative production planning of supply chain under price and demand uncertainty. Eur J Oper Res 215(3):590–603

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Logistics, University of Maribor, Mariborska cesta 7, 3000, Celje, Slovenia

    Roman Gumzej

  2. Department of Logistics and Supply Chains, University of National and World Economy, Studentski Grad “Hristo Botev”, 1700, Sofia, Bulgaria

    Miroslava Rakovska

Authors
  1. Roman Gumzej
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Miroslava Rakovska
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Miroslava Rakovska .

Editor information

Editors and Affiliations

  1. Faculty of Engineering Management, Poznan University of Technology, Poznan, Poland

    Katarzyna Grzybowska

  2. Concordia University, Montreal, QC, Canada

    Anjali Awasthi

  3. Department of Industrial and Systems Engineering, University of Tennessee, Knoxville, TN, USA

    Rapinder Sawhney

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Gumzej, R., Rakovska, M. (2020). Simulation Modeling and Analysis for Sustainable Supply Chains. In: Grzybowska, K., Awasthi, A., Sawhney, R. (eds) Sustainable Logistics and Production in Industry 4.0. EcoProduction. Springer, Cham. https://doi.org/10.1007/978-3-030-33369-0_9

Download citation

Publish with us

Policies and ethics

Search

Navigation