IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

VisTHAA: A Statistical Tool for Comparison of Heuristics

VisTHAA: A Statistical Tool for Comparison of Heuristics
View Sample PDF
Author(s): Laura Cruz-Reyes (National Mexican Institute of Technology, Mexico), Mercedes Pérez Villafuerte (National Mexican Institute of Technology, Mexico), Marcela Quiroz-Castellanos (National Mexican Institute of Technology, Mexico), Claudia Gómez (National Mexican Institute of Technology, Mexico), Nelson Rangel Valdez (National Mexican Institute of Technology, Mexico), César Medina Trejo (National Mexican Institute of Technology, Mexico) and Enith Martínez-Cruz (National Mexican Institute of Technology, Mexico)
Copyright: 2016
Pages: 27
Source title: Handbook of Research on Military, Aeronautical, and Maritime Logistics and Operations
Source Author(s)/Editor(s): Alberto Ochoa-Zezzatti (Juarez City University, Mexico), Jöns Sánchez (Consejo Nacional De Ciencie Y Tecnologia (CONACYT), Mexico), Miguel Gastón Cedillo-Campos (Transportation Systems and Logistics National Laboratory, Mexican Institute of Transportation, Mexico) and Margain de Lourdes (Polytechnic University of Aguascalientes, Mexico)
DOI: 10.4018/978-1-4666-9779-9.ch008

Purchase

View VisTHAA: A Statistical Tool for Comparison of Heuristics on the publisher's website for pricing and purchasing information.

Abstract

In this chapter, a scientific tool designed to facilitate fair comparisons of heuristics is introduced. Making a fair comparison of the performance of different algorithms is a general problem for the heuristic community. Most of the works on experimental analysis of heuristic algorithms have been focused on tabular comparisons of experimental results over standard sets of benchmark instances. However, from a statistical point of view, and according to the experimental design theory, a minimum requirement to compare heuristic algorithms is the use of non-parametric tests. Non-parametric tests can be used for comparing algorithms whose results represent average values, in spite of the inexistence of relationships between them, and explicit conditions of normality, among others. The proposed tool, referred to as VisTHAA, incorporates four non-parametric statistical tests to facilitate the comparative analysis of heuristics. As a case study, VisTHAA is applied to analyze the published results for the best state-of-the-art algorithms that solve the one-dimensional Bin Packing Problem.

Related Content

Anna Piekarczyk. © 2020. 17 pages.
Nick Chandler. © 2020. 18 pages.
Mihaela Preskar, Simona Šarotar Žižek. © 2020. 19 pages.
Jelena Nikolić, Dejana Zlatanović. © 2020. 26 pages.
Tjaša Štrukelj, Matjaž Mulej, Simona Sternad Zabukovšek. © 2020. 21 pages.
Vojko Potocan, Niksa Alfirevic, Zlatko Nedelko. © 2020. 26 pages.
Rainhart Lang, Irma Rybnikova. © 2020. 23 pages.
Body Bottom