A Generalization of a Theorem of Arrow, Barankin and Blackwell to a Nonconvex Case

The paper presents a generalization of a known density theorem of Arrow, Barankin, and Blackwell for properly efficient points defined as support points of sets with respect to monotonically increasing sublinear functions. This result is shown to hold for nonconvex sets of a reflexive Banach space partially ordered by a Bishop–Phelps cone. Citation Department of … Read more

Equilibria on the Day-Ahead Electricity Market

In the energy sector, there has been a transition from monopolistic to oligopolistic situations (pool markets); each time more companies’ optimization revenues depend on the strategies of their competitors. The market rules vary from country to country. In this work, we model the Iberian Day-Ahead Duopoly Market and find exactly which are the outcomes (Nash … Read more

A Dynamic Traveling Salesman Problem with Stochastic Arc Costs

We propose a dynamic traveling salesman problem (TSP) with stochastic arc costs motivated by applications, such as dynamic vehicle routing, in which a decision’s cost is known only probabilistically beforehand but is revealed dynamically before the decision is executed. We formulate the problem as a dynamic program (DP) and compare it to static counterparts to … Read more

A Fair, Sequential Multiple Objective Optimization Algorithm

In multi-objective optimization the objective is to reach a point which is Pareto ecient. However we usually encounter many such points and choosing a point amongst them possesses another problem. In many applications we are required to choose a point having a good spread over all objective functions which is a direct consequence of the … Read more

Optimal Execution Under Jump Models For Uncertain Price Impact

In the execution cost problem, an investor wants to minimize the total expected cost and risk in the execution of a portfolio of risky assets to achieve desired positions. A major source of the execution cost comes from price impacts of both the investor’s own trades and other concurrent institutional trades. Indeed price impact of … Read more

Some criteria for error bounds in set optimization

We obtain sufficient and/or necessary conditions for global/local error bounds for the distances to some sets appeared in set optimization studied with both the set approach and vector approach (sublevel sets, constraint sets, sets of {\it all } Pareto efficient/ Henig proper efficient/super efficient solutions, sets of solutions {\it corresponding to one} Pareto efficient/Henig proper … Read more

Bounds for nested law invariant coherent risk measures

With every law invariant coherent risk measure is associated its conditional analogue. In this paper we discuss lower and upper bounds for the corresponding nested (composite) formulations of law invariant coherent risk measures. In particular, we consider the Average Value-at-Risk and comonotonic risk measures. Article Download View Bounds for nested law invariant coherent risk measures

Effective Strategies to Teach Operations Research to Non-Mathematics Majors

Operations Research (OR) is the discipline of applying advanced analytical methods to help make better decisions (Horner (2003)). OR is characterized by its broad applicability and its interdisciplinary nature. Currently, in addition to mathematics, many other undergraduate programs such as management sciences, business, economics, electrical engineering, civil engineering, chemical engineering, and related fields, have incorporated … Read more

POST-PARETO ANALYSIS FOR MULTIOBJECTIVE PARABOLIC CONTROL SYSTEMS

In this paper is presented the problem of optimizing a functional over a Pareto control set associated with a convex multiobjective control problem in Hilbert spaces, namely parabolic system. This approach generalizes for this setting some results obtained in finite dimensions. Some examples are presented. General optimality results are obtained, and a special attention is … Read more

A note on the convergence of the SDDP algorithm

In this paper we are interested in the convergence analysis of the Stochastic Dual Dynamic Algorithm (SDDP) algorithm in a general framework, and regardless of whether the underlying probability space is discrete or not. We consider a convex stochastic control program not necessarily linear and the resulting dynamic programming equation. We prove under mild assumptions … Read more