Configurable DSS for uncertainty management by fuzzy sets

[EN] In this paper, we propose a Configurable Model Based DSS capable of dealing with generic problems being modeled by Linear Programming (LP) and by Fuzzy Sets (FS) in a deterministic and uncertain context, respectively. The DSS assumes the transformation of the original model with fuzzy coefficients into an equivalent crisp model where the fuzzy coefficients are represented as alpha-parametric values, which can vary in a predefined interval based on the alpha parameter. Through the DSS, solutions obtained by solving the deterministic model and the equivalent crisp model for different alpha-values are compared based on the objectives and performance parameters defined by the Decision Maker (DM). Due to the uncertainty in data, expected performance of solutions can change under real situations. The DSS allows simulating future real situations by generating different projections of uncertain parameters. New performance of previously generated solutions can be tested under these hypothetical real situations by means a third model (Model for the Real Performance Assessment). Finally, the DM can choose the solution to be implemented taking into account the performance of solutions under planned and real uncertainty.Alemany Díaz, MDM.; Boza, A.; Ortiz Bas, Á.; Vicente S. Fuertes-Miquel (2016). Configurable DSS for uncertainty management by fuzzy sets. Procedia Computer Science. 83:1019-1024. doi:10.1016/j.procs.2016.04.217S101910248

Affordable identification and modelling of uncertain design specifications when introducing new technologies in space applications

When introducing new technologies in space products, both the uncertainties regarding technology feasibility and the way in which the technology affects the product development process hinder the early establishment of appropriate engineering specifications. Failing to establish product specifications during conceptual stages leads to problems discovered during later phases of the product development process, when design and process changes are the most expensive.This thesis proposes a digital holistic design platform and a method of constraints replacement for a cost- and time-efficient identification of specification uncertainties when designing space products with new technologies. The digital platform and methods have been developed and tested through industrial case studies featuring the introduction of new technologies for on-orbit applications. Most of these studies were performed in the context of, but are not limited to, the introduction of additive manufacturing.The platform and proposed constraints replacement method are based on function modeling strategies (for modeling product architecture and requirements during conceptual design phases), coupled with activity modeling strategies (for modeling the impact of product architecture on product development schedules and costs). The platform and method enable the identification and assessment of unknown uncertainties, thereby reducing the likelihood of expensive redesign processes during later development phases.Moreover, they enable the inclusion of multidisciplinary design trade-offs during conceptual stages and encourage the establishment of a culture of uncertainty seeking and effective data documentation and transfer

CBR and MBR techniques: review for an application in the emergencies domain

The purpose of this document is to provide an in-depth analysis of current reasoning engine practice and the integration strategies of Case Based Reasoning and Model Based Reasoning that will be used in the design and development of the RIMSAT system. RIMSAT (Remote Intelligent Management Support and Training) is a European Commission funded project designed to: a.. Provide an innovative, 'intelligent', knowledge based solution aimed at improving the quality of critical decisions b.. Enhance the competencies and responsiveness of individuals and organisations involved in highly complex, safety critical incidents - irrespective of their location. In other words, RIMSAT aims to design and implement a decision support system that using Case Base Reasoning as well as Model Base Reasoning technology is applied in the management of emergency situations. This document is part of a deliverable for RIMSAT project, and although it has been done in close contact with the requirements of the project, it provides an overview wide enough for providing a state of the art in integration strategies between CBR and MBR technologies.Postprint (published version

A Food Packaging Use Case for Argumentation

International audienceWithin the framework of the European project EcoBioCap (ECOefficient BIOdegradable Composite Advanced Packaging), aiming at conceiving the next generation of food packagings, we introduce an argumentation-based tool for management of conflicting viewpoints between preferences expressed by the involved parties (food and packaging industries, health and waste management authorities, consumers, etc.). In this paper we recall briefly the principles underlying the reasoning process, and we detail the main functionalities and the architecture of the argumentation tool covering the overall reasoning steps starting from formal representation of text arguments and ending by extraction of justified preferences. Finally, we detail its operational functioning through a real life case study to determine the justifiable choices between recyclable, compostable and biodegradable packaging materials based on stakeholders’ arguments

Context-Aware Framework for Performance Tuning via Multi-action Evaluation

Context-aware systems perform adaptive changes in several ways. One way is for the system developers to encompass all possible context changes in a context-aware application and embed them into the system. However, this may not suit situations where the system encounters unknown contexts. In such cases, system inferences and adaptive learning are used whereby the system executes one action and evaluates the outcome to self-adapts/self-learns based on that. Unfortunately, this iterative approach is time-consuming if high number of actions needs to be evaluated. By contrast, our framework for context-aware systems finds the best action for unknown context through concurrent multi-action evaluation and self-adaptation which reduces significantly the evolution time in comparison to the iterative approach. In our implementation we show how the context-aware multi-action system can be used for a context-aware evaluation for database performance tuning

Experience and potential

"...authored by the participants of the IDRC and UNU/IIST workshop in Macau