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

Informatively optimal levels of confidence for mesurement uncertainty

The conception of dimensional perfection and based on principles of qualimetry and information theory the criterion of informational optimality have been used for analyzing modeling functions of measurement. By means of variances of uncertainty contributions, transformed into their relative weights, the possibility of determining informatively rational and optimal levels of confidence for expanded uncertainty has … Read more

Welfare-Maximizing Correlated Equilibria using Kantorovich Polynomials with Sparsity

We propose an algorithm that computes the epsilon-correlated equilibria with global-optimal (i.e., maximum) expected social welfare for single stage polynomial games. We first derive an infinite-dimensional formulation of epsilon-correlated equilibria using Kantorovich polynomials and re-express it as a polynomial positivity constraint. In addition, we exploit polynomial sparsity to achieve a leaner problem formulation involving Sum-Of-Squares … Read more

Managing Operational and Financing Decisions to Meet Consumption Targets

We study dynamic operational decision problems where risky cash flows are being resolved over a finite planning horizon. Financing decisions via lending and borrowing are available to smooth out consumptions over time with the goal of achieving some prescribed consumption targets. Our target-oriented decision criterion is based on the aggregation of Aumann and Serrano (2008) … Read more

Simulation Optimization for the Stochastic Economic Lot Scheduling Problem

We study simulation optimization methods for the stochastic economic lot scheduling problem. In contrast to prior research, we focus on methods that treat this problem as a black box. Based on a large-scale numerical study, we compare approximate dynamic programming with a global search for parameters of simple control policies. We propose two value function … Read more

A quadratically convergent Newton method for vector optimization

We propose a Newton method for solving smooth unconstrained vector optimization problems under partial orders induced by general closed convex pointed cones. The method extends the one proposed by Fliege, Grana Drummond and Svaiter for multicriteria, which in turn is an extension of the classical Newton method for scalar optimization. The steplength is chosen by … Read more