Search results for "Optimal decision"
showing 7 items of 17 documents
A Generalization of the Mean-Variance Analysis
2008
In this paper we consider a decision maker whose utility function has a kink at the reference point with different functions below and above this reference point. We also suppose that the decision maker generally distorts the objective probabilities. First we show that the expected utility function of this decision maker can be approximated by a function of mean and partial moments of distribution. This "mean-partial moments" utility generalizes not only the mean-variance utility of Tobin and Markowitz, but also the mean-semivariance utility of Markowitz. Then, in the spirit of Arrow and Pratt, we derive an expression for a risk premium when risk is small. Our analysis shows that a decision…
Solving Non-Stationary Bandit Problems by Random Sampling from Sibling Kalman Filters
2010
Published version of an article from Lecture Notes in Computer Science. Also available at SpringerLink: http://dx.doi.org/10.1007/978-3-642-13033-5_21 The multi-armed bandit problem is a classical optimization problem where an agent sequentially pulls one of multiple arms attached to a gambling machine, with each pull resulting in a random reward. The reward distributions are unknown, and thus, one must balance between exploiting existing knowledge about the arms, and obtaining new information. Dynamically changing (non-stationary) bandit problems are particularly challenging because each change of the reward distributions may progressively degrade the performance of any fixed strategy. Alt…
Practical Financial Optimization: A Library of GAMS Models
2010
In Practical Financial Optimization: A Library of GAMS Models, the authors provide a diverse set of models for portfolio optimization, based on the General Algebraic Modelling System. 'GAMS' consists of a language which allows a high-level, algebraic representation of mathematical models and a set of solvers --- numerical algorithms --- to solve them. The system was developed in response to the need for powerful and flexible front-end tools to manage large, real-life models. The work begins with an overview of the structure of the GAMS language, and discusses issues relating to the management of data in GAMS models. The authors provide models for mean-variance portfolio optimization which a…
Deriving Reference Decisions
1998
To solve a statistical decision problem from a Bayesian viewpoint, the decision maker must specify a probability distribution on the parameter space, his prior distribution. In order to analyze the influence of this prior distribution on the solution of the problem, Bernardo (1981) proposed to compare the results with those that one would obtain by using that prior distribution which maximizes the useful experimental information, thus introducing the concept of reference decision. This definition is too involved for most of the problems usually found in practice. Here we analyze situations in which it is possible to simplify the definition of the reference decision, and we provide condition…
Retail pricing decisions and product category competitive structure
2010
This study addresses the use of demand forecasting techniques by retailers to support their decision making. Specifically, the authors propose a pricing decision support model for retailers to estimate optimal prices, whose output depends on the configuration of a supporting measurement model. The measurement model is a demand function that relates sales and prices within the category; optimal prices are those whose effects on demand and retail margins maximize the category's profitability. This investigation focuses particularly on the role of competitive structure, such that the authors consider two types of price competition asymmetries for demand forecasting: those depending on the bran…
Accelerated Bayesian learning for decentralized two-armed bandit based decision making with applications to the Goore Game
2012
Published version of an article in the journal: Applied Intelligence. Also available from the publisher at: http://dx.doi.org/10.1007/s10489-012-0346-z The two-armed bandit problem is a classical optimization problem where a decision maker sequentially pulls one of two arms attached to a gambling machine, with each pull resulting in a random reward. The reward distributions are unknown, and thus, one must balance between exploiting existing knowledge about the arms, and obtaining new information. Bandit problems are particularly fascinating because a large class of real world problems, including routing, Quality of Service (QoS) control, game playing, and resource allocation, can be solved …
Multi-Criteria Decision Making support system for pancreatic islet transplantation
2011
Pancreatic islet transplantation consists of replacing insulin-producing cells to restore normal glycemia in diabetic patients. This is a minimal invasive procedure that has been proved successful. Unfortunately unpredictability of islet transplant outcome remains a frustrating and costly issue limiting the clinical implementation of this procedure. Multiple variables are involved in the procedure and assessment is subjective to individual operators. The aim of this study was to generate a system expressing the probability of transplant success in relation to four classes of identified variables (donor, organ, isolation and recipient). We have proposed the utilization of Multi-Criteria Deci…