منابع مشابه
Data-driven Inverse Optimization with Incomplete Information
In data-driven inverse optimization an observer aims to learn the preferences of an agent who solves a parametric optimization problem depending on an exogenous signal. Thus, the observer seeks the agent’s objective function that best explains a historical sequence of signals and corresponding optimal actions. We formalize this inverse optimization problem as a distributionally robust program m...
متن کاملData-driven inverse optimization with imperfect information
In data-driven inverse optimization an observer aims to learn the preferences of an agent who solves a parametric optimization problem depending on an exogenous signal. Thus, the observer seeks the agent’s objective function that best explains a historical sequence of signals and corresponding optimal actions. We focus here on situations where the observer has imperfect information, that is, wh...
متن کاملInverse DEA Model with Fuzzy Data for Output Estimation
In this paper, we show that inverse Data Envelopment Analysis (DEA) models can be used to estimate output with fuzzy data for a Decision Making Unit (DMU) when some or all inputs are increased and deficiency level of the unit remains unchanged.
متن کاملBayesian Entropic Inverse Theory Approach to Implied Option Pricing with Noisy Data
A popular approach to nonparametric option pricing is the Minimum Cross Entropy (MCE) method based on minimization of the relative Kullback-Leibler entropy of the price density distribution and a given reference density, with observable option prices serving as constraints. When market prices are noisy, the MCE method tends to overfit the data and often becomes unstable. We propose a non-parame...
متن کاملNoisy Derivative-free Optimization with Value Suppression
Derivative-free optimization has shown advantage in solving sophisticated problems such as policy search, when the environment is noise-free. Many real-world environments are noisy, where solution evaluations are inaccurate due to the noise. Noisy evaluation can badly injure derivative-free optimization, as it may make a worse solution looks better. Sampling is a straightforward way to reduce n...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Operations Research
سال: 2018
ISSN: 0030-364X,1526-5463
DOI: 10.1287/opre.2017.1705