The knowledge exploited to tackle difficult problems is probably the main theme of the papers selected for this fifth edition of the International Workshop on Hybrid Metaheuristics. Indeed, in most of the papers a specific combination of metaheuristics and other solving techniques is presented for tackling a particular relevant constrained optimization problem, such as fiber optic networks, timetabling and freight train scheduling problems. The quest for solvers which can successfully and efficiently handle relevant problems is the main motivation for research in metaheuristics: it is important to keep this in mind so as to clearly state our research goals and methodology. The question arises as to what is the definition of relevant problems and a possible answer is that any useful and even just interesting or funny problem can be considered as scientifically relevant. The research goal of solving relevant problems does not require practitioners to assemble some software code and, with a little faith in alchemy, hope that the outcome is a reasonably good solution. On the contrary, this research must be grounded on a scientific method and on technological skills. That is why it is so important to support the assessment of an algorithm’s performance with a sound methodology. This requires studying theoretical models for describing properties of the hybrid metaheuristics, and to be open to other communities and to compare our achievements with theirs.

Proceedings of HM 2008 -- Fifth International Workshop on Hybrid Metaheuristics

ROLI, ANDREA;
2008

Abstract

The knowledge exploited to tackle difficult problems is probably the main theme of the papers selected for this fifth edition of the International Workshop on Hybrid Metaheuristics. Indeed, in most of the papers a specific combination of metaheuristics and other solving techniques is presented for tackling a particular relevant constrained optimization problem, such as fiber optic networks, timetabling and freight train scheduling problems. The quest for solvers which can successfully and efficiently handle relevant problems is the main motivation for research in metaheuristics: it is important to keep this in mind so as to clearly state our research goals and methodology. The question arises as to what is the definition of relevant problems and a possible answer is that any useful and even just interesting or funny problem can be considered as scientifically relevant. The research goal of solving relevant problems does not require practitioners to assemble some software code and, with a little faith in alchemy, hope that the outcome is a reasonably good solution. On the contrary, this research must be grounded on a scientific method and on technological skills. That is why it is so important to support the assessment of an algorithm’s performance with a sound methodology. This requires studying theoretical models for describing properties of the hybrid metaheuristics, and to be open to other communities and to compare our achievements with theirs.
213
9783540884385
M.J.Blesa; C.Blum; C.Cotta; A.J.Fernández; J.E.Gallardo; A.Roli; M.Sampels
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11585/62578
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