Solving unstructured classification problems with multicriteria decision aiding

Tese de mestrado integrado. Engenharia Electrotécnica e de Computadores (Automação). Universidade do Porto. Faculdade de Engenharia. 201

A Temporal Distributed Group Decision Support System Based on Multi-Criteria Analysis

Decision support consists of proposing tasks and projects by taking into account temporal constraints and the use of resources with the aim of finding a compromise solution between several alternatives. Indeed, on the one hand, centralized resolution systems and methods are generally inappropriate to the real case because of the local unavailability of decision makers. On the other hand, the data of the decisional problem are generally poorly expressed in a negotiation environment. Other techniques and approaches treat the same decision-making problem and impose a distributed vision for coherent decisions. For this purpose, Multi-Agent Systems (MAS) allow modeling a distributed resolution of the group decision support problem. In this article, we propose a new model of a multi-criteria group decision support system based on a multi-agent system modeling a spatial problem. We consider that each decision maker is assimilated to an agent that has a decision-making autonomy, in which he interacts with other agents in the debate through a negotiation process in order to reach an acceptable compromise. In this study, we propose coordination mechanisms among agents to highlight the simulated negotiation. Therefore, the proposed system finds a solution before fixed deadlines’ time expire. We experiment the suggested negotiation model to solve the decisional problem of spatial localization in territory planning

Multicriteria sorting method based on global and local search for supplier segmentation

The aim of this research is to develop a robust multicriteria method to classify suppliers into ordered categories and its validation in real contexts. The proposed technique is based on a property of net flows of the PROMETHEE method and uses global and local search concepts, which are common in the optimisation field. The results obtained are compared to those from the most cited sorting algorithm, and an empirical validation and sensitivity analysis is performed using real supplier evaluation data. Furthermore, it does not require additional information from decision-makers as other sorting algorithms do for assigning incomparable or indifferent alternatives to groups. An extension of the silhouette concept from data mining is also contributed to measure the quality of ordered classes. Both contributions are easy to apply and integrate into decision support systems for automated decisions in the supply chain management. Finally, this practical approach is also useful to classify customers and any type of alternatives or actions into ordered categories, which have an increasing number of real applications

PROMETHEE-SAPEVO-M1 a Hybrid Approach Based on Ordinal and Cardinal Inputs: Multi-Criteria Evaluation of Helicopters to Support Brazilian Navy Operations

This paper presents a new approach based on Multi-Criteria Decision Analysis (MCDA), named PROMETHEE-SAPEVO-M1, through its implementation and feasibility related to the decision-making process regarding the evaluation of helicopters of attack of the Brazilian Navy. The proposed methodology aims to present an integration of ordinal evaluation into the cardinal procedure from the PROMETHEE method, enabling to perform qualitative and quantitative data and generate the criteria weights by pairwise evaluation, transparently. The modeling provides three models of preference analysis, as partial, complete, and outranking by intervals, along with an intra-criterion analysis by veto threshold, enabling the analysis of the performance of an alternative in a specific criterion. As a demonstration of the application, is carried out a case study by the PROMETHEE-SAPEVO-M1 web platform, addressing a strategic analysis of attack helicopters to be acquired by the Brazilian Navy, from the need to be evaluating multiple specifications with different levels of importance within the context problem. The modeling implementation in the case study is made in detail, first performing the alternatives in each criterion and then presenting the results by three different models of preference analysis, along with the intra-criterion analysis and a rank reversal procedure. Moreover, is realized a comparison analysis to the PROMETHEE method, exploring the main features of the PROMETHEE-SAPEVO-M1. Moreover, a section of discussion is presented, exposing some features and main points of the proposal. Therefore, this paper provides a valuable contribution to academia and society since it represents the application of an MCDA method in the state of the art, contributing to the decision-making resolution of the most diverse real problems.This research was funded by Centre for Research & Development in Mechanical Engineering (CIDEM), School of Engineering of Porto (ISEP), Polytechnic of Porto, Rua Dr. António Bernardino de Almeida, 431 4249-015 Porto, Portugal.info:eu-repo/semantics/publishedVersio

Neuro-fuzzy resource forecast in site suitability assessment for wind and solar energy: a mini review

Abstract:Site suitability problems in renewable energy studies have taken a new turn since the advent of geographical information system (GIS). GIS has been used for site suitability analysis for renewable energy due to its prowess in processing and analyzing attributes with geospatial components. Multi-criteria decision making (MCDM) tools are further used for criteria ranking in the order of influence on the study. Upon location of most appropriate sites, the need for intelligent resource forecast to aid in strategic and operational planning becomes necessary if viability of the investment will be enhanced and resource variability will be better understood. One of such intelligent models is the adaptive neuro-fuzzy inference system (ANFIS) and its variants. This study presents a mini-review of GIS-based MCDM facility location problems in wind and solar resource site suitability analysis and resource forecast using ANFIS-based models. We further present a framework for the integration of the two concepts in wind and solar energy studies. Various MCDM techniques for decision making with their strengths and weaknesses were presented. Country specific studies which apply GIS-based method in site suitability were presented with criteria considered. Similarly, country-specific studies in ANFIS-based resource forecasts for wind and solar energy were also presented. From our findings, there has been no technically valid range of values for spatial criteria and the analytical hierarchical process (AHP) has been commonly used for criteria ranking leaving other techniques less explored. Also, hybrid ANFIS models are more effective compared to standalone ANFIS models in resource forecast, and ANFIS optimized with population-based models has been mostly used. Finally, we present a roadmap for integrating GIS-MCDM site suitability studies with ANFIS-based modeling for improved strategic and operational planning

Multi-Criteria Decision Making in software development:a systematic literature review

Abstract. Multiple Criteria Decision Making is a formal approach to assist decision makers to select the best solutions among multiple alternatives by assessing criteria which are relatively precise but generally conflicting. The utilization of MCDM are quite popular and common in software development process. In this study, a systematic literature review which includes creating review protocol, selecting primary study, making classification schema, extracting data and other relevant steps was conducted. The objective of this study are making a summary about the state-of-the-art of MCDM in software development process and identifying the MCDM methods and MCDM problems in software development by systematically structuring and analyzing the literature on those issues. A total of 56 primary studies were identified after the review, and 33 types of MCDM methods were extracted from those primary studies. Among them, AHP was defined as the most frequent used MCDM methods in software development process by ranking the number of primary studies which applied it in their studies, and Pareto optimization was ranked in the second place. Meanwhile, 33 types of software development problems were identified. Components selection, design concepts selection and performance evaluation became the three most frequent occurred problems which need to be resolved by MCDM methods. Most of those MCDM problems were found in software design phase. There were many limitations to affect the quality of this study; however, the strictly-followed procedures of SLR and mass data from thousands of literature can still ensure the validity of this study, and this study is also able to provide the references when decision makers want to select the appropriate technique to cope with the MCDM problems