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A multi-objective evolutionary optimization approach for an integrated location-inventory distribution network problem under vendor-managed inventory systems

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  • Shu-Hsien Liao
  • Chia-Lin Hsieh
  • Yu-Siang Lin

Abstract

In this paper, we propose an integrated model to incorporate inventory control decisions—such as economic order quantity, safety stock and inventory replenishment decisions—into typical facility location models, which are used to solve the distribution network design problem. A simultaneous model is developed considering a stochastic demand, modeling also the risk poling phenomenon. Multi-objective decision analysis is adopted to allow use of a performance measurement system that includes cost, customer service levels (fill rates), and flexibility (responsive level). This measurement system provides more comprehensive measurement of supply chain system performance than do traditional, single measure approaches. A multi-objective location-inventory model which permits a comprehensive trade-off evaluation for multi-objective optimization is initially presented. More specifically, a multiobjective evolutionary algorithm is developed to determine the optimal facility location portfolio and inventory control parameters in order to reach best compromise of these conflicting criteria. An experimental study using practical data was then illustrated for the possibility of the proposed approach. Computational results have presented promising solutions in solving a practical-size problem with 50 buyers and 15 potential DCs and proved to be an innovative and efficient approach for so called difficult-to-solve problems. Copyright Springer Science+Business Media, LLC 2011

Suggested Citation

  • Shu-Hsien Liao & Chia-Lin Hsieh & Yu-Siang Lin, 2011. "A multi-objective evolutionary optimization approach for an integrated location-inventory distribution network problem under vendor-managed inventory systems," Annals of Operations Research, Springer, vol. 186(1), pages 213-229, June.
    • Handle: RePEc:spr:annopr:v:186:y:2011:i:1:p:213-229:10.1007/s10479-010-0801-3
    DOI: 10.1007/s10479-010-0801-3
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    Cited by:

    1. Gang Wang & Angappa Gunasekaran & Eric W. T. Ngai, 2018. "Distribution network design with big data: model and analysis," Annals of Operations Research, Springer, vol. 270(1), pages 539-551, November.
    2. Pourya Pourhejazy & Oh Kyoung Kwon, 2016. "The New Generation of Operations Research Methods in Supply Chain Optimization: A Review," Sustainability, MDPI, vol. 8(10), pages 1-23, October.
    3. Barros, Júlio & Cortez, Paulo & Carvalho, M. Sameiro, 2021. "A systematic literature review about dimensioning safety stock under uncertainties and risks in the procurement process," Operations Research Perspectives, Elsevier, vol. 8(C).
    4. Shuangyan Li & Xialian Li & Dezhi Zhang & Lingyun Zhou, 2017. "Joint Optimization of Distribution Network Design and Two-Echelon Inventory Control with Stochastic Demand and CO2 Emission Tax Charges," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-22, January.
    5. Morteza Lalmazloumian & Kuan Yew Wong & Kannan Govindan & Devika Kannan, 2016. "A robust optimization model for agile and build-to-order supply chain planning under uncertainties," Annals of Operations Research, Springer, vol. 240(2), pages 435-470, May.
    6. Ahmadi-Javid, Amir & Hoseinpour, Pooya, 2015. "A location-inventory-pricing model in a supply chain distribution network with price-sensitive demands and inventory-capacity constraints," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 82(C), pages 238-255.
    7. N. Hoseini Monjezi & S. Nobakhtian, 2022. "An inexact multiple proximal bundle algorithm for nonsmooth nonconvex multiobjective optimization problems," Annals of Operations Research, Springer, vol. 311(2), pages 1123-1154, April.
    8. Sina Nayeri & Mahdieh Tavakoli & Mehrab Tanhaeean & Fariborz Jolai, 2022. "A robust fuzzy stochastic model for the responsive-resilient inventory-location problem: comparison of metaheuristic algorithms," Annals of Operations Research, Springer, vol. 315(2), pages 1895-1935, August.
    9. Harris, Irina & Mumford, Christine L. & Naim, Mohamed M., 2014. "A hybrid multi-objective approach to capacitated facility location with flexible store allocation for green logistics modeling," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 66(C), pages 1-22.
    10. Peyman Taki & Farnaz Barzinpour & Ebrahim Teimoury, 2016. "Risk-pooling strategy, lead time, delivery reliability and inventory control decisions in a stochastic multi-objective supply chain network design," Annals of Operations Research, Springer, vol. 244(2), pages 619-646, September.
    11. Mohammad Fathian & Javid Jouzdani & Mehdi Heydari & Ahmad Makui, 2018. "Location and transportation planning in supply chains under uncertainty and congestion by using an improved electromagnetism-like algorithm," Journal of Intelligent Manufacturing, Springer, vol. 29(7), pages 1447-1464, October.

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