Developing the infrastructures for preventing non-communicable diseases is one of the most important goals of healthcare context in recent years. In this regard, the number and capacity of preventive healthcare facilities as well as assignment of customers to facilities should be determined for each region. Besides the accessibility, the utility of customers is a determinative factor in partici...

This article deals with constrained multi-objective optimization problems. The main purpose of the article is to investigate relationships between constrained and unconstrained multi-objective optimization problems. Under suitable assumptions (e.g., generalized convexity assumptions) we derive a characterization of the set of (strictly, weakly) efficient solutions of a constrained multi-objecti...

This paper deals with preference representation and elicitation in the context of multiattribute utility theory under risk. Assuming the decision maker behaves according to the EU model, we investigate the elicitation of generalized additively decomposable utility functions on a product set (GAI-decomposable utilities). We propose a general elicitation procedure based on a new graphical model c...

Bayesian learning is widely used in many applied datamodelling problems and is often accompanied with approximation schemes since it requires intractable computation of the posterior distributions. In this study, we focus on the two approximation methods, the variational Bayes and the local variational approximation. We show that the variational Bayes approach for statistical models with latent...

logical form or covert syntax is a syntactic level introduced in recent generative approaches. using the ideas of first-order predicate logic, it interprets the strings whose elements cannot move in s–structure, because an element moves if it does not acquire its necessary scope. but unlike the predicate logic, logical form is based on syntactic principles and rules. therefore, logical form is ...

The present paper addresses the issue of optimization of reliability acceptance criteria for components of complex engineered systems with given criterion to acceptable system risk. To this end, the paper first describes how complex engineered systems may be modelled hierarchically by use of Bayesian probabilistic networks. The Bayesian probabilistic network serves as a function relating the re...

Abstract We discuss stochastic optimization problems under distributional ambiguity. The uncertainty is captured by considering an entire family of distributions. Because we assume the existence data, can consider confidence regions for different estimators parameters Based on definition appropriate estimator in interior resulting region, propose a new data-driven problem. This approach applies...