A branch-and-cut method for dynamic decision making under joint chance constraints

• Autores: Minjiao Zhang, Simge Küçükyavuz, Saumya Goel
• Localización: Management science: journal of the Institute for operations research and the management sciences, ISSN 0025-1909, Vol. 60, Nº. 5, 2014, págs. 1317-1333
• Idioma: inglés
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• Resumen

  • In this paper, we consider a finite-horizon stochastic mixed-integer program involving dynamic decisions under a constraint on the overall performance or reliability of the system. We formulate this problem as a multistage (dynamic) chance-constrained program, whose deterministic equivalent is a large-scale mixed-integer program. We study the structure of the formulation and develop a branch-and-cut method for its solution. We illustrate the efficacy of the proposed model and method on a dynamic inventory control problem with stochastic demand in which a specific service level must be met over the entire planning horizon. We compare our dynamic model with a static chance-constrained model, a dynamic risk-averse optimization model, a robust optimization model, and a pseudo-dynamic approach and show that significant cost savings can be achieved at high service levels using our model.