Processing, Please wait...

  • Home
  • About Us
  • Search:
  • Advanced Search

Growing Science » International Journal of Industrial Engineering Computations » The non-stationary stochastic lot-sizing with joint replenishment under (R, S) policy and the heuristics

Journals

  • IJIEC (777)
  • MSL (2643)
  • DSL (690)
  • CCL (528)
  • USCM (1092)
  • ESM (421)
  • AC (562)
  • JPM (293)
  • IJDS (952)
  • JFS (101)
  • HE (32)
  • SCI (26)

IJIEC Volumes

    • Volume 1 (17)
      • Issue 1 (9)
      • Issue 2 (8)
    • Volume 2 (68)
      • Issue 1 (12)
      • Issue 2 (20)
      • Issue 3 (20)
      • Issue 4 (16)
    • Volume 3 (76)
      • Issue 1 (9)
      • Issue 2 (15)
      • Issue 3 (20)
      • Issue 4 (12)
      • Issue 5 (20)
    • Volume 4 (50)
      • Issue 1 (14)
      • Issue 2 (10)
      • Issue 3 (12)
      • Issue 4 (14)
    • Volume 5 (47)
      • Issue 1 (13)
      • Issue 2 (12)
      • Issue 3 (12)
      • Issue 4 (10)
    • Volume 6 (39)
      • Issue 1 (7)
      • Issue 2 (12)
      • Issue 3 (10)
      • Issue 4 (10)
    • Volume 7 (47)
      • Issue 1 (10)
      • Issue 2 (14)
      • Issue 3 (10)
      • Issue 4 (13)
    • Volume 8 (30)
      • Issue 1 (9)
      • Issue 2 (7)
      • Issue 3 (8)
      • Issue 4 (6)
    • Volume 9 (32)
      • Issue 1 (9)
      • Issue 2 (6)
      • Issue 3 (7)
      • Issue 4 (10)
    • Volume 10 (34)
      • Issue 1 (8)
      • Issue 2 (10)
      • Issue 3 (8)
      • Issue 4 (8)
    • Volume 11 (36)
      • Issue 1 (9)
      • Issue 2 (8)
      • Issue 3 (9)
      • Issue 4 (10)
    • Volume 12 (29)
      • Issue 1 (9)
      • Issue 2 (6)
      • Issue 3 (8)
      • Issue 4 (6)
    • Volume 13 (41)
      • Issue 1 (10)
      • Issue 2 (8)
      • Issue 3 (10)
      • Issue 4 (13)
    • Volume 14 (50)
      • Issue 1 (11)
      • Issue 2 (15)
      • Issue 3 (9)
      • Issue 4 (15)
    • Volume 15 (55)
      • Issue 1 (19)
      • Issue 2 (15)
      • Issue 3 (12)
      • Issue 4 (9)
    • Volume 16 (75)
      • Issue 1 (12)
      • Issue 2 (15)
      • Issue 3 (19)
      • Issue 4 (29)
    • Volume 17 (51)
      • Issue 1 (21)
      • Issue 2 (30)

Keywords

Supply chain management(168)
Jordan(165)
Vietnam(151)
Customer satisfaction(120)
Performance(115)
Supply chain(112)
Service quality(98)
Competitive advantage(97)
Tehran Stock Exchange(94)
SMEs(89)
optimization(87)
Sustainability(86)
Artificial intelligence(85)
Financial performance(84)
Trust(83)
TOPSIS(83)
Job satisfaction(81)
Genetic Algorithm(78)
Factor analysis(78)
Social media(78)


» Show all keywords

Authors

Naser Azad(82)
Zeplin Jiwa Husada Tarigan(66)
Mohammad Reza Iravani(64)
Endri Endri(45)
Muhammad Alshurideh(42)
Hotlan Siagian(40)
Dmaithan Almajali(37)
Jumadil Saputra(36)
Muhammad Turki Alshurideh(35)
Ahmad Makui(33)
Barween Al Kurdi(32)
Hassan Ghodrati(31)
Basrowi Basrowi(31)
Sautma Ronni Basana(31)
Mohammad Khodaei Valahzaghard(30)
Shankar Chakraborty(29)
Ni Nyoman Kerti Yasa(29)
Haitham M. Alzoubi(28)
Sulieman Ibraheem Shelash Al-Hawary(28)
Prasadja Ricardianto(28)


» Show all authors

Countries

Iran(2192)
Indonesia(1311)
Jordan(813)
India(793)
Vietnam(510)
Saudi Arabia(478)
Malaysia(444)
China(231)
United Arab Emirates(226)
Thailand(160)
United States(114)
Ukraine(110)
Turkey(110)
Egypt(106)
Peru(94)
Canada(93)
Morocco(86)
Pakistan(85)
United Kingdom(80)
Nigeria(78)


» Show all countries

International Journal of Industrial Engineering Computations

ISSN 1923-2934 (Online) - ISSN 1923-2926 (Print)
Quarterly Publication
Volume 16 Issue 3 pp. 709-720 , 2025

The non-stationary stochastic lot-sizing with joint replenishment under (R, S) policy and the heuristics Pages 709-720 Right click to download the paper Download PDF

Authors: Jufeng Yang, Sujian Li

DOI: 10.5267/j.ijiec.2025.4.003

Keywords: Lot-sizing, Non-stationary stochastic demands, Joint replenishment, (R, S) policy, Heuristic

Abstract: This study investigates for the first time the non-stationary stochastic lot-sizing problem involving multi-dealer joint replenishment under the policy (R, S) without fill rate constraints. The planning horizon for each dealer is divided into the replenishment cycle series, accounting for the lead time associated with each joint replenishment cycle. A shortest path model is developed. Through mathematical analysis, the safety stock variables are eliminated, and the multiple variables are reduced to replenishment variables only. The stochastic problem is converted to the deterministic dynamic lot-sizing through expectation analysis. Furthermore, the MLS-MRS heuristic is proposed based on Robinson's Left-Right shift (LS-RS) heuristic by adding a module, the positive cost-saving family shifts. This algorithm improves the optimal solution and notably greatly increases the search speed.

How to cite this paper
Yang, J & Li, S. (2025). The non-stationary stochastic lot-sizing with joint replenishment under (R, S) policy and the heuristics.International Journal of Industrial Engineering Computations , 16(3), 709-720.

Refrences
Boctor, F. F., Laporte, G., & Renaud, J. (2004). Models and algorithms for the dynamic-demand joint replenishment problem. International Journal of Production Research, 42, 2667 - 2678. Bookbinder, J. H., & Tan, J.-Y. (1988). Strategies for the Probabilistic Lot-Sizing Problem with Service-Level Constraints. Management Science, 34(9), 1096-1108. https://doi.org/10.1287/mnsc.34.9.1096 Eisenhut, P. S. (1975). A Dynamic Lot Sizing Algorithm with Capacity Constraints. A I I E Transactions, 7(2), 170-176. https://doi.org/10.1080/05695557508974999 Erenguc, S. S. (1988). Multiproduct dynamic lot-sizing model with coordinated replenishments. Naval Research Logistics (NRL), 35(1), 1-22. https://doi.org/https://doi.org/10.1002/nav.3220350102 Federgruen, A., & Tzur, M. (1994). The Joint Replenishment Problem with Time-Varying Costs and Demands: Efficient, Asymptotic and ε-Optimal Solutions. Operations Research, 42(6), 1067-1086. https://doi.org/10.1287/opre.42.6.1067 Fogarty, D. W., & Barringer, R. L. (1987). Joint order release decisions under dependent demand [Article]. Production and inventory management Washington, D.C., 28(1), 55-61. Goyal, S. K. (1973). Determination of Economic Packaging Frequency for Items Jointly Replenished. Management Science, 20, 232-235. Iyogun, P. (1991). Heuristic Methods for the Multi-product Dynamic Lot Size Problem. Journal of the Operational Research Society, 42(10), 889-894. https://doi.org/10.1057/jors.1991.169 Joneja, D. (1990). The Joint Replenishment Problem: New Heuristics and Worst Case Performance Bounds. Operations Research, 38(4), 711-723. https://doi.org/10.1287/opre.38.4.711 Kao, E. P. C. (1979). A Multi-Product Dynamic Lot-Size Model with Individual and Joint Set-up Costs. Operations Research, 27(2), 279-289. https://doi.org/10.1287/opre.27.2.279 Lambrecht, M. R., & Vanderveken, H. (1979). Heuristic Procedures for the Single Operation, Multi-Item Loading Problem. A I I E Transactions, 11(4), 319-326. https://doi.org/10.1080/05695557908974478 Ma, X., Rossi, R., & Archibald, T. W. (2022). Approximations for non-stationary stochastic lot-sizing under (s,Q)-type policy. European Journal of Operational Research, 298(2), 573-584. https://doi.org/10.1016/j.ejor.2021.06.013 Özen, U., Doğru, M. K., & Armagan Tarim, S. (2012). Static-dynamic uncertainty strategy for a single-item stochastic inventory control problem. Omega, 40(3), 348-357. https://doi.org/10.1016/j.omega.2011.08.002 Robinson, E. P., & Gao, L.-L. (1996). A Dual Ascent Procedure for Multiproduct Dynamic Demand Coordinated Replenishment with Backlogging. Management Science, 42, 1556-1564. Robinson, E. P., Narayanan, A., & Gao, L. L. (2007). Effective heuristics for the dynamic demand joint replenishment problem. Journal of the Operational Research Society, 58(6), 808-815. https://doi.org/10.1057/palgrave.jors.2602197 Silver, E. (1978). Inventory control under a probabilistic time-varying, demand pattern. A I I E Transactions, 10(4), 371-379. https://doi.org/10.1080/05695557808975228 Silver E, K. P. (1988). More on ‘Joint order release decisions under dependent demand. Prod Invent Mngt J(29), 71-72. Tarim, S. A., Dogˇru, M. K., Özen, U., & Rossi, R. (2011). An efficient computational method for a stochastic dynamic lot-sizing problem under service-level constraints. European Journal of Operational Research, 215(3), 563-571. https://doi.org/10.1016/j.ejor.2011.06.034 Tarim, S. A., & Kingsman, B. G. (2004). The stochastic dynamic production/inventory lot-sizing problem with service-level constraints. International Journal of Production Economics, 88(1), 105-119. https://doi.org/10.1016/s0925-5273(03)00182-8 Tarim, S. A., & Kingsman, B. G. (2006). Modelling and computing (Rn,Sn) policies for inventory systems with non-stationary stochastic demand. European Journal of Operational Research, 174(1), 581-599. https://doi.org/10.1016/j.ejor.2005.01.053 Tempelmeier, H. (2007). On the stochastic uncapacitated dynamic single-item lotsizing problem with service level constraints. European Journal of Operational Research, 181(1), 184-194. https://doi.org/10.1016/j.ejor.2006.06.009 ter Haseborg, F. (1982). On the optimality of joint ordering policies in a multi-product dynamic lot size model with individual and joint set-up costs. European Journal of Operational Research, 9(1), 47-55. https://doi.org/https://doi.org/10.1016/0377-2217(82)90009-1 Tunc, H., Kilic, O. A., Tarim, S. A., & Rossi, R. (2018). An Extended Mixed-Integer Programming Formulation and Dynamic Cut Generation Approach for the Stochastic Lot-Sizing Problem. INFORMS Journal on Computing, 30(3), 492-506. https://doi.org/10.1287/ijoc.2017.0792 Visentin, A., Prestwich, S., Rossi, R., & Tarim, S. A. (2021). Computing optimal (R,s,S) policy parameters by a hybrid of branch-and-bound and stochastic dynamic programming. European Journal of Operational Research, 294(1), 91-99. https://doi.org/10.1016/j.ejor.2021.01.012 Visentin, A., Prestwich, S., Rossi, R., & Tarim, S. A. (2023). Stochastic dynamic programming heuristic for the (R,s,S) policy parameters computation. Computers & Operations Research, 158. https://doi.org/10.1016/j.cor.2023.106289 Wagner, H. M., & Whitin, T. M. (1958). Dynamic Version of the Economic Lot Size Model. Management Science, 5(1), 89-96. https://doi.org/10.1287/mnsc.5.1.89 Xiang, M., Rossi, R., Martin-Barragan, B., & Tarim, S. A. (2018). Computing non-stationary (s, S) policies using mixed integer linear programming. European Journal of Operational Research, 271(2), 490-500. https://doi.org/10.1016/j.ejor.2018.05.030
  • 0
  • 1
  • 2
  • 3
  • 4
  • 5

Journal: International Journal of Industrial Engineering Computations | Year: 2025 | Volume: 16 | Issue: 3 | Views: 391 | Reviews: 0

Related Articles:
  • You are entitled to access the full text of this document Integrating VMI i ...
  • A matheuristic based solution approach for the general lot sizing and sched ...
  • A multi supplier lot sizing strategy using dynamic programming
  • Vendor-buyer ordering policy when demand is trapezoidal
  • Supplier selection and order lot sizing using dynamic programming

Add Reviews

Name:*
E-Mail:
Review:
Bold Italic Underline Strike | Align left Center Align right | Insert smilies Insert link URLInsert protected URL Select color | Add Hidden Text Insert Quote Convert selected text from selection to Cyrillic (Russian) alphabet Insert spoiler
winkwinkedsmileam
belayfeelfellowlaughing
lollovenorecourse
requestsadtonguewassat
cryingwhatbullyangry
Security Code: *
Include security image CAPCHA.
Refresh Code

® 2010-2026 GrowingScience.Com