scholarly journals Pareto Dominance-Based Algorithms With Ranking Methods for Many-Objective Optimization

IEEE Access ◽  
2017 ◽  
Vol 5 ◽  
pp. 11043-11053 ◽  
Author(s):  
Vikas Palakonda ◽  
Rammohan Mallipeddi
Keyword(s):  
Ranking Methods ◽  
Pareto Dominance

scholarly journals Ranking Multi-Metric Scientific Achievements Using a Concept of Pareto Optimality

Mathematics ◽  
2020 ◽  
Vol 8 (6) ◽  
pp. 956 ◽  
Author(s):  
Shahryar Rahnamayan ◽  
Sedigheh Mahdavi ◽  
Kalyanmoy Deb ◽  
Azam Asilian Bidgoli
Keyword(s):  
Pareto Optimality ◽  
Ranking Methods ◽  
Pareto Dominance ◽  
Optimal Weights ◽  
Scientific Datasets ◽  
Ranking Strategy ◽  
Resolution Problem ◽  
Number Of Publications ◽  
Statistical Metrics ◽  
Scientific Achievements

The ranking of multi-metric scientific achievements is a challenging task. For example, the scientific ranking of researchers utilizes two major types of indicators; namely, number of publications and citations. In fact, they focus on how to select proper indicators, considering only one indicator or combination of them. The majority of ranking methods combine several indicators, but these methods are faced with a challenging concern—the assignment of suitable/optimal weights to the targeted indicators. Pareto optimality is defined as a measure of efficiency in the multi-objective optimization which seeks the optimal solutions by considering multiple criteria/objectives simultaneously. The performance of the basic Pareto dominance depth ranking strategy decreases by increasing the number of criteria (generally speaking, when it is more than three criteria). In this paper, a new, modified Pareto dominance depth ranking strategy is proposed which uses some dominance metrics obtained from the basic Pareto dominance depth ranking and some sorted statistical metrics to rank the scientific achievements. It attempts to find the clusters of compared data by using all of indicators simultaneously. Furthermore, we apply the proposed method to address the multi-source ranking resolution problem which is very common these days; for example, there are several world-wide institutions which rank the world’s universities every year, but their rankings are not consistent. As our case studies, the proposed method was used to rank several scientific datasets (i.e., researchers, universities, and countries) for proof of concept.

Ranking of European Union Member States Based on the Level of Knowledge Created by the Research and Development Sector

2014 ◽  
Vol 9 (1) ◽  
pp. 47-56
Author(s):  
Krystyna Romaniuk
Keyword(s):  
European Union ◽  
Research And Development ◽  
Knowledge Creation ◽  
Union Member ◽  
Political Life ◽  
Ranking Methods ◽  
Member States ◽  
Management Paradigms ◽  
Level Of Knowledge ◽  
European Union Member States

The contemporary era is characterized by revolutionary changes in the economy, technological progress, social and political life. Globalization exerts pressure on businesses and entire economies to increase their competitive strength which is defined as the ability to create knowledge. Knowledge creation and management became the new management paradigms. The responsibility for knowledge creation rests mainly upon the research and development sector. The aim of this study was to rank European Union Member States based on the level of knowledge created by their respective research and development sectors and to identify knowledge creation leaders. The analysis relied on EUROSTAT data for 2007-2011 and linear ranking methods with a reference standard. Our results indicate that Western European and Scandinavian countries are the leaders in the area of knowledge creation.

Pareto Set as a Model for Dispatching Resources in Emergency Centres (Preprint)

2018 ◽  
Author(s):  
Ricardo Guedes ◽  
Vasco Furtado ◽  
Tarcísio Pequeno ◽  
Joel Rodrigues
Keyword(s):  
Operational Research ◽  
Real Data ◽  
Pareto Set ◽  
Multi Objective Optimization ◽  
Pareto Dominance ◽  
Four Dimensions ◽  
Multi Objective ◽  
The Best Approximation ◽  
One Year ◽  
The Cost

UNSTRUCTURED The article investigates policies for helping emergency-centre authorities for dispatching resources aimed at reducing goals such as response time, the number of unattended calls, the attending of priority calls, and the cost of displacement of vehicles. Pareto Set is shown to be the appropriated way to support the representation of policies of dispatch since it naturally fits the challenges of multi-objective optimization. By means of the concept of Pareto dominance a set with objectives may be ordered in a way that guides the dispatch of resources. Instead of manually trying to identify the best dispatching strategy, a multi-objective evolutionary algorithm coupled with an Emergency Call Simulator uncovers automatically the best approximation of the optimal Pareto Set that would be the responsible for indicating the importance of each objective and consequently the order of attendance of the calls. The scenario of validation is a big metropolis in Brazil using one-year of real data from 911 calls. Comparisons with traditional policies proposed in the literature are done as well as other innovative policies inspired from different domains as computer science and operational research. The results show that strategy of ranking the calls from a Pareto Set discovered by the evolutionary method is a good option because it has the second best (lowest) waiting time, serves almost 100% of priority calls, is the second most economical, and is the second in attendance of calls. That is to say, it is a strategy in which the four dimensions are considered without major impairment to any of them.

Sign in / Sign up

Export Citation Format

Share Document