Large corporations usually cover their capital and operating expenses by issuing bonds with fixed rates different maturities. This paper proposes a multistage stochastic programming (MSP) model multiple objectives to optimize bond issuance satisfying the three common of corporate managers, as follows: (i) Minimizing expected discounted cost under cash liquidity financial leverage risk constrain...

Decision making under uncertainty includes reassessing and reevaluating risk after initial decisions. To this end, it is essential to consider a governing value process track its evolution over time. The paper, “Risk-Averse Stochastic Programming: Time Consistency Optimal Stopping,” by Pichler, Liu, Shapiro, develops consistent framework consolidating optimal stopping. paper the notion of time ...

In this paper, we propose a new model for designing integrated forward/reverse logistics based on pricing policy in direct and indirect sales channel. The proposed model includes producers, disposal center, distributers and final customers. We assumed that the location of final customers is fixed. First, a deterministic mixed integer linear programming model is developed for integrated logistic...

We introduce Stochastic Dynamic Cutting Plane (StoDCuP), an extension of the Dual Programming (SDDP) algorithm to solve multistage stochastic convex optimization problems. At each iteration, builds lower bounding affine functions not only for cost-to-go functions, as SDDP does, but also some or all nonlinear cost and constraint functions. show almost sure convergence StoDCuP. inexact variant St...

We consider totally unimodular multistage stochastic programs, that is, multistage stochastic programs whose extensive-form constraint matrices are totally unimodular. We establish several sufficient conditions and identify examples that have arisen in the literature.

Stochastic optimization, especially multistage models, is well known to be computationally excruciating. In this paper, we introduce the concept of semi-complete recourse in the context of stochastic programming as a less restrictive condition compared to complete recourse and propose methods for approximating multistage stochastic programs with risk constraints and semi-complete recourse. We e...

The algebraic modelling languages (AML) have gained wide acceptance and use in Mathematical Programming by researchers and practitioners. At a basic level, stochastic programming models can be defined using these languages by constructing their deterministic equivalent. Unfortunately, this leads to very large model data instances. We propose a direct approach in which the random values of the m...

Economic processes are very often influenced simultaneously by a decision parameter (that can be chosen according to conditions) and a random factor. Since mostly it is necessary to determine the decision parameter without knowledge of a random element realization, a deterministic optimization problem has to be defined. This deterministic problem can usually depend on an “underlying” probabilit...

We present a multistage model for allocation of financial resources to bond indices in different currencies. The model was tested on historical data of interest and exchange rates. We compare a two-stage and a three-stage stochastic programming model from a financial performance point of view. For solving two-stage and three-stage stochastic programs the interior point method (IPM) in the frame...