Málstofa í tölfræði
Fyrirlesari: Guðmundur Einarsson, M.S. student of Statistics, University of Iceland
Titill: Discussion on evolutionary algorithms in optimization
Staðsetning: Room V-157 in building VR-II on the UI campus
Tími: Thursday, April 3rd 2014, at 12:00 to 13:00.
Abstract:
Two papers will be discussed. First, a paper entitled „Metaheuristics-the metaphor exposed“ by K. Sörensen. Summary of paper:
In recent years, the field of combinatorial optimization has witnessed a true tsunami of “novel” metaheuristic methods, most of them based on a metaphor of some natural or man-made process. The behavior of virtually any species of insects, the flow of water, musicians playing together — it seems that no idea is too far-fetched to serve as inspiration to launch yet another metaheuristic. In this paper we will argue that this line of research is threatening to lead the area of metaheuristics away from scientific rigour. We will examine the historical context that gave rise to the increasing use of metaphors as inspiration and justification for the development of new methods, discuss the reasons for the vulnerability of the metaheuristics field to this line of research, and point out its fallacies. At the same time, truly innovative research of high quality is being performed as well. We conclude the paper by discussing some of the properties of this research and by pointing out some of the most promising research avenues for the field of metaheuristics.
Secondly, a paper entitled „On the Hunt: Competitive Coevolution as a Metaheuristic“ by Guðmundur Einarsson, Tómas Philip Rúnarsson and Gunnar Stefánsson. Summary of paper:
A predator prey model for competitive coevolution is used as a metaheuristic. Two scenarios are created. In each scenario the predator genetic setup consists of parameters for optimization procedures. The prey genetic setup consists of starting points for the optimization of a specific function. A sampling method is explored for the relative fitness assessment where the number of fitness evaluations can be controlled similar to K-fold relative fitness assessment. The historical evolution of the prey is explored as a diagnostics tool for multimodality.Statistics colloquium talk
Speaker: Guðmundur Einarsson, M.S. student of Statistics, University of Iceland
Title: Discussion on evolutionary algorithms in optimization
Location: Room V-157 in building VR-II on the UI campus
Time: Thursday, April 3rd 2014, at 12:00 to 13:00.
Abstract:
Two papers will be discussed. First, a paper entitled „Metaheuristics-the metaphor exposed“ by K. Sörensen. Summary of paper:
In recent years, the field of combinatorial optimization has witnessed a true tsunami of “novel” metaheuristic methods, most of them based on a metaphor of some natural or man-made process. The behavior of virtually any species of insects, the flow of water, musicians playing together — it seems that no idea is too far-fetched to serve as inspiration to launch yet another metaheuristic. In this paper we will argue that this line of research is threatening to lead the area of metaheuristics away from scientific rigour. We will examine the historical context that gave rise to the increasing use of metaphors as inspiration and justification for the development of new methods, discuss the reasons for the vulnerability of the metaheuristics field to this line of research, and point out its fallacies. At the same time, truly innovative research of high quality is being performed as well. We conclude the paper by discussing some of the properties of this research and by pointing out some of the most promising research avenues for the field of metaheuristics.
Secondly, a paper entitled „On the Hunt: Competitive Coevolution as a Metaheuristic“ by Guðmundur Einarsson, Tómas Philip Rúnarsson and Gunnar Stefánsson. Summary of paper:
A predator prey model for competitive coevolution is used as a metaheuristic. Two scenarios are created. In each scenario the predator genetic setup consists of parameters for optimization procedures. The prey genetic setup consists of starting points for the optimization of a specific function. A sampling method is explored for the relative fitness assessment where the number of fitness evaluations can be controlled similar to K-fold relative fitness assessment. The historical evolution of the prey is explored as a diagnostics tool for multimodality.