The concept of scenarios is typically employed for modeling random parameters in a multi-period stochastic programming model, and scenarios are constructed via a tree structure.
In this paper, we explicitly consider the underlying uncertainties with a complex multi-period stochastic programming model that captures the trade-offs between the objectives.
In this paper, we compare the two types of multi-period stochastic optimization models, and clarify that the hybrid model can evaluate and control risk better than the scenario tree model using some numerical tests.
In this optimization, the effect of equipment failures on system operation performance and costs is analyzed by system reliability, and uncertain steam and power demands are formulated by a multi-period stochastic programming.
In multi-period stochastic formulation of classical mean variance portfolio optimization problem, an investor makes an investment decision based on expectations and/or scenarios up to some intermediate times prior to the horizon and, consequently, rebalances or restructures the portfolio.
To obtain an optimal design of the IUHSN reflecting the reality, we develop a mathematical model which is formulated as multi-period stochastic mixed integer linear programming concerning uncertain raw material prices.
In this paper, a bi-criterion, multi-period, stochastic mixed-integer linear programming model is proposed to address the optimal design and planning of hydrocarbon biorefinery supply chains under supply and demand uncertainties.
A multi-period stochastic planning model with finite number of realizations has been developed and implemented for a supply and distribution network of a petroleum organization operating under uncertain market conditions.
Topics include deterministic inventory models (EOQ, Power-of-two policies, ELS, serial and assembly networks), the Newsvendor model, multi-period stochastic inventory theory, serial and multi-echelon models, approximation algorithms, batch ordering and lost-sales models, infinitesimal perturbation analysis, distribution-free inventory theory, models for joint pricing and inventory decisions.
Najafi et al. (2013) developed a multi-objective, multi-mode, multi-commodity, and multi-period stochastic model to manage the logistics of both commodities and injured people in the earthquake response phase.
A hybrid simulation/tree multi-period stochastic programming model for optimal asset allocation.
