Experiences with stochastic algorithms for a class of constrained global optimisation problems

The solution of a variety of classes of global optimisation problems is required in the implementation of a framework for sensitivity analysis in multicriteria decision analysis. These problems have linear constraints, some of which have a particular structure, and a variety of objective functions, which may be smooth or non-smooth. The context in which they arise implies a need for a single, robust solution method. The literature contains few experimental results relevant to such a need. We report on our experience with the implementation of three stochastic algorithms for global optimisation: the multi-level single linkage algorithm, the topographical algorithm and the simulated annealing algorithm. Issues relating to their implementation and use to solve practical problems are discussed. Computational results suggest that, for the class of problems considered, simulated annealing performs well

Gradient Methods for Solving Stackelberg Games

Stackelberg Games are gaining importance in the last years due to the raise of Adversarial Machine Learning (AML). Within this context, a new paradigm must be faced: in classical game theory, intervening agents were humans whose decisions are generally discrete and low dimensional. In AML, decisions are made by algorithms and are usually continuous and high dimensional, e.g. choosing the weights of a neural network. As closed form solutions for Stackelberg games generally do not exist, it is mandatory to have efficient algorithms to search for numerical solutions. We study two different procedures for solving this type of games using gradient methods. We study time and space scalability of both approaches and discuss in which situation it is more appropriate to use each of them. Finally, we illustrate their use in an adversarial prediction problem.Comment: Accepted in ADT Conference 201

Functional impairment of systemic scleroderma patients with digital ulcerations: results from the DUO Registry

OBJECTIVES: Digital ulcers (DUs) are frequent manifestations of systemic scleroderma (SSc). This study assessed functional limitations due to DUs among patients enrolled in the Digital Ulcer Outcome (DUO) Registry, an international, multicentre, observational registry of SSc patients with DU disease. METHODS: Patients completed at enrolment a DU-specific functional assessment questionnaire with a 1-month recall period, measuring impairment in work and daily activities, and hours of help needed from others. Physician-reported clinical parameters were used to describe the population. For patients who completed at least part of the questionnaire, descriptive analyses were performed for overall results, and stratified by number of DUs at enrolment. RESULTS: This study included 2327 patients who completed at least part of the questionnaire. For patients with 0, 1–2, and ≥3 DUs at enrolment, mean overall work impairment during the prior month among employed/self-employed patients was 28%, 42%, and 48%, respectively. Across all included patients, ability to perform daily activities was impaired on average by 35%, 54%, and 63%, respectively. Patients required a mean of 2.0, 8.7, and 8.8 hours of paid help and 17.0, 35.9, and 63.7 hours of unpaid help, respectively, due to DUs in the prior month. Patients with DUs had more complications and medication use than patients with no DUs. CONCLUSIONS: With increasing number of DUs, SSc patients reported more impairment in work and daily activities and required more support from others

A Review and Classification of Approaches for Dealing with Uncertainty in Multi-Criteria Decision Analysis for Healthcare Decisions

The Author(s) 2015. This article is published with open access at Springerlink.com Abstract Multi-criteria decision analysis (MCDA) is increasingly used to support decisions in healthcare involving multiple and conflicting criteria. Although uncertainty is usually carefully addressed in health eco-nomic evaluations, whether and how the different sources of uncertainty are dealt with and with what methods in MCDA is less known. The objective of this study is to review how uncertainty can be explicitly taken into account in MCDA and to discuss which approach may be appro-priate for healthcare decision makers. A literature review was conducted in the Scopus and PubMed databases. Two reviewers independently categorized studies according to research areas, the type of MCDA used, and the approach used to quantify uncertainty. Selected full text articles wer

A framework for participatory budget elaboration support

Participatory budgets are becoming increasingly popular in many municipalities all around the world. The underlying idea is to allow citizens to participate in the allocation of a municipal budget. Little decision support methodology is used in this type of activities, frequently based on physical meetings and some kind of voting mechanism. We describe models and methods to support the elaboration of a participatory budget. We model this problem as one of resource allocation, in which citizens attempt to maximize group satisfaction in view of multiple criteria, subject to, possibly, other constraints. Based on a negotiation approach, we propose a general methodology to deal with such a problem. © 2008 Operational Research Society Ltd. All rights reserved

Sensitivity Analysis

Estadística e Investigación Operativ