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Dynamic Probabilistic Lot-Sizing with Service Level Constraints

Goel, Saumya

Abstract Details

2011, Master of Science, Ohio State University, Industrial and Systems Engineering.
We consider inventory control problems with stochastic demand in which a specific service level must be met. We assume that demand and cost distributions over the planning horizon are finite, discrete and non-stationary. We formulate this problem as a chance-constrained program, whose deterministic equivalent is a large-scale mixed-integer program (MIP). We study the structure of the formulations and develop methods for solving them efficiently. We add mixing cuts to tighten these formulations and propose new valid inequalities. We also decompose these large-scale mixed integer programs using Benders decomposition technique and branch-and-price-and-cut method, both of which could incorporate mixing cuts to improve their performance.
Simge Küçükyavuz (Advisor)
Marc Posner (Committee Member)
Suvrajeet Sen (Committee Member)

Recommended Citations

Citations

  • Goel, S. (2011). Dynamic Probabilistic Lot-Sizing with Service Level Constraints [Master's thesis, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1306865399

    APA Style (7th edition)

  • Goel, Saumya. Dynamic Probabilistic Lot-Sizing with Service Level Constraints. 2011. Ohio State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1306865399.

    MLA Style (8th edition)

  • Goel, Saumya. "Dynamic Probabilistic Lot-Sizing with Service Level Constraints." Master's thesis, Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1306865399

    Chicago Manual of Style (17th edition)