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Journal articles on the topic 'Capacitated Lot Sizing Problem'

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Published: 4 June 2021
Last updated: 7 February 2022

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1

Zhang, Minjiao. "Capacitated lot-sizing problem with outsourcing." Operations Research Letters 43, no. 5 (September 2015): 479–83. http://dx.doi.org/10.1016/j.orl.2015.06.007.

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2

Suerie, Christopher, and Hartmut Stadtler. "The Capacitated Lot-Sizing Problem with Linked Lot Sizes." Management Science 49, no. 8 (August 2003): 1039–54. http://dx.doi.org/10.1287/mnsc.49.8.1039.16406.

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3

Sharma, Renduchintala Raghavendra Kumar, Priyank Sinha, and Mananjay Kumar Verma. "Computationally Efficient Problem Reformulations for Capacitated Lot Sizing Problem." American Journal of Operations Research 08, no. 04 (2018): 312–22. http://dx.doi.org/10.4236/ajor.2018.84018.

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4

Billington, Peter J. "The Capacitated Multi-Item Dynamic Lot-Sizing Problem." IIE Transactions 18, no. 2 (June 1986): 217–19. http://dx.doi.org/10.1080/07408178608975350.

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5

Patil, Amitkumar, Gaurav Kumar Badhotiya, Bimal Nepal, and Gunjan Soni. "Modeling Multi-Plant Capacitated Lot Sizing Problem with Interplant Transfer." International Journal of Mathematical, Engineering and Management Sciences 6, no. 3 (June 1, 2021): 961–74. http://dx.doi.org/10.33889/ijmems.2021.6.3.057.

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Lot sizing models involve operational and tactical decisions. These decisions may entail multi-level production processes such as assembly operations with multiple plants and limited capacities. Lot sizing problems are widely recognized as NP-hard problems therefore difficult to solve, especially the ones with multiple plants and capacity constraints. The level of complexity rises to an even higher level when there is an interplant transfer between the plants. This paper presents a Genetic Algorithm (GA) based solution methodology applied to large scale multi-plant capacitated lot sizing problem with interplant transfer (MPCLSP-IT). Although the GA has been a very effective and widely accepted meta-heuristic approach used to solve large scale complex problems, it has not been employed for MPCLSP-IT problem. This paper solves the MPCLSP-IT problem in large scale instances by using a genetic algorithm, and in doing so successfully obtains a better solution in terms of computation time when compared to the results obtained by the other methods such as Lagrangian relaxation, greedy randomized adaptive search procedure (GRASP) heuristics, and GRASP-path relinking techniques used in extant literature.
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6

Li, Chung-Lun, and Qingying Li. "Polynomial-Time Solvability of Dynamic Lot Size Problems." Asia-Pacific Journal of Operational Research 33, no. 03 (June 2016): 1650018. http://dx.doi.org/10.1142/s0217595916500184.

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There has been a lot of research on dynamic lot sizing problems with different nonlinear cost structures due to capacitated production, minimum order quantity requirements, availability of quantity discounts, etc. Developing optimal solutions efficiently for dynamic lot sizing models with nonlinear cost functions is a challenging topic. In this paper, we present a set of sufficient conditions such that if a single-item dynamic lot sizing problem satisfies these conditions, then the existence of a polynomial-time solution method for the problem is guaranteed. Several examples are presented to demonstrate the use of these sufficient conditions.
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7

You, Meng, Yiyong Xiao, Siyue Zhang, Shenghan Zhou, Pei Yang, and Xing Pan. "Modeling the Capacitated Multi-Level Lot-Sizing Problem under Time-Varying Environments and a Fix-and-Optimize Solution Approach." Entropy 21, no. 4 (April 7, 2019): 377. http://dx.doi.org/10.3390/e21040377.

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In this study, we investigated the time-varying capacitated lot-sizing problem under a fast-changing production environment, where production factors such as the setup costs, inventory-holding costs, production capacities, or even material prices may be subject to continuous changes during the entire planning horizon. Traditional lot-sizing theorems and algorithms, which often assume a constant production environment, are no longer fit for this situation. We analyzed the time-varying environment of today’s agile enterprises and modeled the time-varying setup costs and the time-varying production capacities. Based on these, we presented two mixed-integer linear programming models for the time-varying capacitated single-level lot-sizing problem and the time-varying capacitated multi-level lot-sizing problem, respectively, with considerations on the impact of time-varying environments and dynamic capacity constraints. New properties of these models were analyzed on the solution’s feasibility and optimality. The solution quality was evaluated in terms of the entropy which indicated that the optimized production system had a lower value than that of the unoptimized one. A number of computational experiments were conducted on well-known benchmark problem instances using the AMPL/CPLEX to verify the proposed models and to test the computational effectiveness and efficiency, which showed that the new models are applicable to the time-varying environment. Two of the benchmark problems were updated with new best-known solutions in the experiments.
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8

Cheng, C. H., M. S. Madan, Y. Gupta, and S. So. "Solving the capacitated lot-sizing problem with backorder consideration." Journal of the Operational Research Society 52, no. 8 (August 2001): 952–59. http://dx.doi.org/10.1057/palgrave.jors.2601166.

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9

Brandimarte, P., A. Alfieri, and R. Levi. "LP-Based Heuristics for the Capacitated Lot Sizing Problem." CIRP Annals 47, no. 1 (1998): 423–26. http://dx.doi.org/10.1016/s0007-8506(07)62866-2.

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10

SOX, CHARLES R., and YUBO GAO. "The capacitated lot sizing problem with setup carry-over." IIE Transactions 31, no. 2 (February 1999): 173–81. http://dx.doi.org/10.1080/07408179908969816.

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11

Madan, Manu S., C. H. Cheng, Eric Yip, and Jaideep Motwani. "An improved heuristic for the Capacitated Lot-Sizing problem." International Journal of Operational Research 7, no. 1 (2010): 90. http://dx.doi.org/10.1504/ijor.2010.029519.

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12

Kang, Jangha. "Capacitated Lot-Sizing Problem with Sequence-Dependent Setup, Setup Carryover and Setup Crossover." Processes 8, no. 7 (July 5, 2020): 785. http://dx.doi.org/10.3390/pr8070785.

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Since setup operations have significant impacts on production environments, the capacitated lot-sizing problem considering arbitrary length of setup times helps to develop flexible and efficient production plans. This study discusses a capacitated lot-sizing problem with sequence-dependent setup, setup carryover and setup crossover. A new mixed integer programming formulation is proposed. The formulation is based on three building blocks: the facility location extended formulation; the setup variables with indices for the starting and the completion time periods; and exponential number of generalized subtour elimination constraints (GSECs). A separation routine is adopted to generate the violated GSECs. Computational experiments show that the proposed formulation outperforms models from the literature.
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13

Akbalik, Ayse, Bernard Penz, and Christophe Rapine. "Capacitated lot sizing problems with inventory bounds." Annals of Operations Research 229, no. 1 (February 21, 2015): 1–18. http://dx.doi.org/10.1007/s10479-015-1816-6.

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14

Li, Shi. "Constant Approximation Algorithm for Nonuniform Capacitated Multi-Item Lot Sizing via Strong Covering Inequalities." Mathematics of Operations Research 45, no. 3 (August 2020): 947–65. http://dx.doi.org/10.1287/moor.2019.1018.

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We study the nonuniform capacitated multi-item lot-sizing problem. In this problem, there is a set of demands over a planning horizon of T discrete time periods, and all demands must be satisfied on time. We can place an order at the beginning of each period s, incurring an ordering cost Ks. In this order, we can order up to Cs units of products. On the other hand, carrying inventory from time to time incurs an inventory holding cost. The goal of the problem is to find a feasible solution that minimizes the sum of ordering and holding costs. Levi et al. [Levi R, Lodi A, Sviridenko M (2008) Approximation algorithms for the capacitated multi-item lot-sizing problem via flow-cover inequalities. Math. Oper. Res. 33(2):461–474.] gave a two-approximation for the problem when the capacities Cs are the same. Extending the result to the case of nonuniform capacities requires new techniques as pointed out in the discussion section of their paper. In this paper, we solve the problem by giving a 10-approximation algorithm for the capacitated multi-item lot-sizing problem with general capacities. The constant approximation is achieved by adding an exponential number of new covering inequalities to the natural facility location–type linear programming (LP) relaxation for the problem. Along the way of our algorithm, we reduce the lot-sizing problem to two generalizations of the classic knapsack-covering problem. We give LP-based constant approximation algorithms for both generalizations via the iterative rounding technique.
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15

Hwang, H. C., W. Jaruphongsa, S. Çetinkaya, and C. Y. Lee. "Capacitated dynamic lot-sizing problem with delivery/production time windows." Operations Research Letters 38, no. 5 (September 2010): 408–13. http://dx.doi.org/10.1016/j.orl.2010.04.009.

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16

Berretta, Regina, and Luiz Fernando Rodrigues. "A memetic algorithm for a multistage capacitated lot-sizing problem." International Journal of Production Economics 87, no. 1 (January 2004): 67–81. http://dx.doi.org/10.1016/s0925-5273(03)00093-8.

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17

Armentano, Vinı́cius A., Paulo M. França, and Franklina M. B. de Toledo. "A network flow model for the capacitated lot-sizing problem." Omega 27, no. 2 (April 1999): 275–84. http://dx.doi.org/10.1016/s0305-0483(98)00045-0.

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18

Saleem, Ramadan, Gürsel A. Süer, and Jing Huang. "Dual-stage genetic algorithm approach for capacitated lot sizing problem." International Journal of Advanced Operations Management 5, no. 4 (2013): 299. http://dx.doi.org/10.1504/ijaom.2013.058887.

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19

Trigeiro, William W. "A Dual-Cost Heuristic For The Capacitated Lot Sizing Problem." IIE Transactions 19, no. 1 (March 1987): 67–72. http://dx.doi.org/10.1080/07408178708975371.

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20

Hartman, Joseph C., İ. Esra Büyüktahtakin, and J. Cole Smith. "Dynamic-programming-based inequalities for the capacitated lot-sizing problem." IIE Transactions 42, no. 12 (September 30, 2010): 915–30. http://dx.doi.org/10.1080/0740817x.2010.504683.

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21

Büyüktahtakın, İ. Esra, and Ning Liu. "Dynamic programming approximation algorithms for the capacitated lot-sizing problem." Journal of Global Optimization 65, no. 2 (August 23, 2015): 231–59. http://dx.doi.org/10.1007/s10898-015-0349-5.

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22

Hwang, Hark-Chin, Hyun-Soo Ahn, and Philip Kaminsky. "Algorithms for the two-stage production-capacitated lot-sizing problem." Journal of Global Optimization 65, no. 4 (December 16, 2015): 777–99. http://dx.doi.org/10.1007/s10898-015-0392-2.

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23

Gansterer, Margaretha, Patrick Födermayr, and Richard F. Hartl. "The capacitated multi-level lot-sizing problem with distributed agents." International Journal of Production Economics 235 (May 2021): 108090. http://dx.doi.org/10.1016/j.ijpe.2021.108090.

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24

Girlich, Eberhard, Michael Höding, Alexander Zaporozhets, and Sergei Chubanov. "A Greedy Algorithm for Capacitated Lot-Sizing Problems." Optimization 52, no. 2 (January 2003): 241–49. http://dx.doi.org/10.1080/0233193031000079801.

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25

Absi, Nabil. "Models and methods for capacitated lot-sizing problems." 4OR 6, no. 3 (November 7, 2007): 311–14. http://dx.doi.org/10.1007/s10288-007-0062-4.

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26

Verma, Mayank, and Renduchintala Raghavendra Kumar Sharma. "Hybrid Formulation of the Multi-Item Capacitated Dynamic Lot Sizing Problem." American Journal of Operations Research 05, no. 06 (2015): 503–13. http://dx.doi.org/10.4236/ajor.2015.56039.

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27

Gao, Yubo. "Capacitated lot sizing problem with setup carry-over: a heuristic procedure." Chinese Journal of Mechanical Engineering (English Edition) 13, supp (2000): 31. http://dx.doi.org/10.3901/cjme.2000.supp.031.

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28

Karimi, B., S. M. T. Fatemi Ghomi, and J. M. Wilson. "The capacitated lot sizing problem: a review of models and algorithms." Omega 31, no. 5 (October 2003): 365–78. http://dx.doi.org/10.1016/s0305-0483(03)00059-8.

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29

Robinson, E. Powell, and F. Barry Lawrence. "Coordinated Capacitated Lot-Sizing Problem with Dynamic Demand: A Lagrangian Heuristic." Decision Sciences 35, no. 1 (February 2004): 25–53. http://dx.doi.org/10.1111/j.1540-5414.2004.02396.x.

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30

de Araujo, Silvio Alexandre, Bert De Reyck, Zeger Degraeve, Ioannis Fragkos, and Raf Jans. "Period Decompositions for the Capacitated Lot Sizing Problem with Setup Times." INFORMS Journal on Computing 27, no. 3 (August 2015): 431–48. http://dx.doi.org/10.1287/ijoc.2014.0636.

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31

Absi, Nabil, and Safia Kedad-Sidhoum. "CAPACITATED LOT-SIZING PROBLEM WITH SETUP TIMES, STOCK AND DEMAND SHORTAGES." IFAC Proceedings Volumes 39, no. 3 (2006): 185–90. http://dx.doi.org/10.3182/20060517-3-fr-2903.00109.

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32

ÖZDAMAR, LINET, and MEHMET ALI BOZYEL. "The capacitated lot sizing problem with overtime decisions and setup times." IIE Transactions 32, no. 11 (November 2000): 1043–57. http://dx.doi.org/10.1080/07408170008967460.

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33

Hindi, K. S. "Computationally efficient solution of the multi-item, capacitated lot-sizing problem." Computers & Industrial Engineering 28, no. 4 (October 1995): 709–19. http://dx.doi.org/10.1016/0360-8352(95)00021-r.

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34

Almeder, Christian, Diego Klabjan, Renate Traxler, and Bernardo Almada-Lobo. "Lead time considerations for the multi-level capacitated lot-sizing problem." European Journal of Operational Research 241, no. 3 (March 2015): 727–38. http://dx.doi.org/10.1016/j.ejor.2014.09.030.

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35

Hardin, Jill R., George L. Nemhauser, and Martin W. P. Savelsbergh. "Analysis of bounds for a capacitated single-item lot-sizing problem." Computers & Operations Research 34, no. 6 (June 2007): 1721–43. http://dx.doi.org/10.1016/j.cor.2005.05.031.

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36

Tempelmeier, Horst, and Timo Hilger. "Linear programming models for a stochastic dynamic capacitated lot sizing problem." Computers & Operations Research 59 (July 2015): 119–25. http://dx.doi.org/10.1016/j.cor.2015.01.007.

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37

Büyüktahtakın, İ. Esra, J. Cole Smith, and Joseph C. Hartman. "Partial objective inequalities for the multi-item capacitated lot-sizing problem." Computers & Operations Research 91 (March 2018): 132–44. http://dx.doi.org/10.1016/j.cor.2017.11.006.

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38

Tempelmeier, Horst, Michael Kirste, and Timo Hilger. "Linear programming models for a stochastic dynamic capacitated lot sizing problem." Computers & Operations Research 91 (March 2018): 258–59. http://dx.doi.org/10.1016/j.cor.2017.11.010.

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39

Wu, Tao, Fan Xiao, Canrong Zhang, Yan He, and Zhe Liang. "The green capacitated multi-item lot sizing problem with parallel machines." Computers & Operations Research 98 (October 2018): 149–64. http://dx.doi.org/10.1016/j.cor.2018.05.024.

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40

Lozano, Sebastian, Juan Larraneta, and Luis Onieva. "Primal-dual approach to the single level capacitated lot-sizing problem." European Journal of Operational Research 51, no. 3 (April 1991): 354–66. http://dx.doi.org/10.1016/0377-2217(91)90311-i.

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41

Duda, Jerzy, and Adam Stawowy. "A variable neighborhood search for multi-family capacitated lot-sizing problem." Electronic Notes in Discrete Mathematics 66 (April 2018): 119–26. http://dx.doi.org/10.1016/j.endm.2018.03.016.

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42

Chen, W. H., and J. M. Thizy. "Analysis of relaxations for the multi-item capacitated lot-sizing problem." Annals of Operations Research 26, no. 1-4 (December 1990): 29–72. http://dx.doi.org/10.1007/bf02248584.

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43

Taş, Duygu, Michel Gendreau, Ola Jabali, and Raf Jans. "A capacitated lot sizing problem with stochastic setup times and overtime." European Journal of Operational Research 273, no. 1 (February 2019): 146–59. http://dx.doi.org/10.1016/j.ejor.2018.07.032.

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44

Fatma, Erika. "MINIMALISASI BIAYA SIMPAN DAN BIAYA SETUP PADA MULTIPLE PRODUK: SIMULASI DENGAN CAPACITATED LOT SIZING PROBLEM." Jurnal Riset Manajemen dan Bisnis (JRMB) Fakultas Ekonomi UNIAT 4, no. 2 (June 12, 2019): 205–14. http://dx.doi.org/10.36226/jrmb.v4i2.260.

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Lot sizing problem in production planning aims to optimize production costs (processing, setup and holding cost) by fulfilling demand and resources capacity costraint. The Capacitated Lot sizing Problem (CLSP) model aims to balance the setup costs and inventory costs to obtain optimal total costs. The object of this study was a plastic component manufacturing company. This study use CLSP model, considering process costs, holding costs and setup costs, by calculating product cycle and setup time. The constraint of this model is the production time capacity and the storage capacity of the finished product. CLSP can reduce the total production cost by 4.05% and can reduce setup time by 46.75%. Keyword: Lot size, CLSP, Total production cost.
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45

Güner Gören, Hacer, and Semra Tunali. "Fix-and-optimize heuristics for capacitated lot sizing with setup carryover and backordering." Journal of Enterprise Information Management 31, no. 6 (October 8, 2018): 879–90. http://dx.doi.org/10.1108/jeim-01-2017-0017.

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PurposeThe capacitated lot sizing problem (CLSP) is one of the most important production planning problems which has been widely studied in lot sizing literature. The CLSP is the extension of the Wagner-Whitin problem where there is one product and no capacity constraints. The CLSP involves determining lot sizes for multiple products on a single machine with limited capacity that may change for each planning period. Determining the right lot sizes has a critical importance on the productivity and success of organizations. The paper aims to discuss these issues.Design/methodology/approachThis study focuses on the CLSP with setup carryover and backordering. The literature focusing on this problem is rather limited. To fill this gap, a number of problem-specific heuristics have been integrated with fix-and-optimize (FOPT) heuristic in this study. The authors have compared the performances of the proposed approaches to that of the commercial solver and recent results in literature. The obtained results have stated that the proposed approaches are efficient in solving this problem.FindingsThe computational experiments have shown that the proposed approaches are efficient in solving this problem.Originality/valueTo address the solution of the CLSP with setup carryover and backordering, a number of heuristic approaches consisting of FOPT heuristic are proposed in this paper.
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46

Testuri, Carlos E., Héctor Cancela, and Víctor M. Albornoz. "A multistage stochastic lot-sizing problem with cancellation and postponement under uncertain demands." RAIRO - Operations Research 55, no. 2 (March 2021): 861–72. http://dx.doi.org/10.1051/ro/2021042.

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A multistage stochastic capacitated discrete procurement problem with lead times, cancellation and postponement is addressed. The problem determines the procurement of a product under uncertain demand at minimal expected cost during a time horizon. The supply of the product is made through the purchase of optional distinguishable orders of fixed size with delivery time. Due to the unveiling of uncertainty over time it is possible to make cancellation and postponement corrective decisions on order procurement. These decisions involve costs and times of implementation. A model of the problem is formulated as an extension of a discrete capacitated lot-sizing problem under uncertain demand and lead times through a multi-stage stochastic mixed-integer linear optimization approach. Valid inequalities are generated, based on a conventional inequalities approach, to tighten the model formulation. Experiments are performed for several problem instances with different uncertainty information structure. Their results allow to conclude that the incorporation of a subset of the generated inequalities favor the model solution.
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47

Brahimi, Nadjib, Stéphane Dauzère-Pérès, and Najib M. Najid. "Capacitated Multi-Item Lot-Sizing Problems with Time Windows." Operations Research 54, no. 5 (October 2006): 951–67. http://dx.doi.org/10.1287/opre.1060.0325.

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48

Xie, Jinxing, and Jiefang Dong. "Heuristic genetic algorithms for general capacitated lot-sizing problems." Computers & Mathematics with Applications 44, no. 1-2 (July 2002): 263–76. http://dx.doi.org/10.1016/s0898-1221(02)00146-3.

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49

Ozdamar, L., and G. Barbarosoglu. "Hybrid Heuristics for the Multi-Stage Capacitated Lot Sizing and Loading Problem." Journal of the Operational Research Society 50, no. 8 (August 1999): 810. http://dx.doi.org/10.2307/3010340.

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50

Jans, Raf, and Zeger Degraeve. "Improved lower bounds for the capacitated lot sizing problem with setup times." Operations Research Letters 32, no. 2 (March 2004): 185–95. http://dx.doi.org/10.1016/j.orl.2003.06.001.

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