Risk neutral and risk averse Stochastic Dual Dynamic Programming method

In this paper we discuss risk neutral and risk averse approaches to multistage (linear) stochastic programming problems based on the Stochastic Dual Dynamic Programming (SDDP) method. We give a general description of the algorithm and present computational studies related to planning of the Brazilian interconnected power system. Citation ArticleDownload View PDF

Error bounds for vector-valued functions on metric spaces

In this paper, we attempt to extend the definition and existing local error bound criteria to vector-valued functions, or more generally, to functions taking values in a normed linear space. Some new primal space derivative-like objects — slopes — are introduced and a classification scheme of error bound criteria is presented. CitationPublished in Vietnam Journal … Read more

Optimizing Trading Decisions for Hydro Storage Systems using Approximate Dual Dynamic Programming

We propose a new approach to optimize operations of hydro storage systems with multiple connected reservoirs which participate in wholesale electricity markets. Our formulation integrates short-term intraday with long-term interday decisions. The intraday problem considers bidding decisions as well as storage operation during the day and is formulated as a stochastic program. The interday problem … Read more

On the Geometry of Acceptability Functionals

Abstract In this paper we discuss continuity properties of acceptability functionals or risk measures. The dependence of the random variable is investigated first. The main contribution and focus of this paper is to study how acceptability functionals vary whenever the underlying probability measure is perturbed. Abstract It turns out that the Wasserstein distance provides a … Read more

Time-inconsistent multistage stochastic programs: martingale bounds

Abstract. It is well known that multistage programs, which maximize expectation or expected utility, allow a dynamic programming formulation, and that other objectives destroy the dynamic programming character of the problem. This paper considers a risk measure at the final stage of a multistage stochastic program. Although these problems are not time consistent, it is … Read more

Informational validity of Fechtner’s experiments outcomes

All manifestations of dimensional harmony in nature and human practice are being always characterized by deviations from golden ratio that often makes their acceptance problematic. On the example of Fechner’s experiments the paper discusses the way of solving this problem, based on informational approach, according to which the informatively optimal permissible deviation from dimensional harmony … Read more

Optimal Toll Design: A Lower Bound Framework for the Asymmetric Traveling Salesman Problem

We propose a framework of lower bounds for the asymmetric traveling salesman problem (TSP) based on approximating the dynamic programming formulation with diff erent basis vector sets. We discuss how several well-known TSP lower bounds correspond to intuitive basis vector choices and give an economic interpretation wherein the salesman must pay tolls as he travels between … Read more

A Primal-Dual Algorithm for Computing a Cost Allocation in the Core of Economic Lot-Sizing Games

We consider the economic lot-sizing game with general concave ordering cost functions. It is well-known that the core of this game is nonempty when the inventory holding costs are linear. The main contribution of this work is a combinatorial, primal-dual algorithm that computes a cost allocation in the core of these games in polynomial time. … Read more

Characterization of local quadratic growth for strong minima in the optimal control of semi-linear elliptic equations

In this article we consider an optimal control problem of a semi-linear elliptic equation, with bound constraints on the control. Our aim is to characterize local quadratic growth for the cost function J in the sense of strong solutions. This means that the function J growths quadratically over all feasible controls whose associated state is … Read more

A semi-discrete in time approximation for a model first order-finite horizon mean field game problem

In this article we consider a model first order mean field game problem, introduced by J.M. Lasry and P.L. Lions. Its solution $(v,m)$ can be obtained as the limit of the solutions of the second order mean field game problems, when the \textit{noise} parameter tends to zero. We propose a semi-discrete in time approximation of … Read more