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Hybrid Metaheuristics: Preface to the proceedings of HM2005
No full textCombinatorial optimization attracted many researchers since more than three decades.
Plenty of classical hard problems have been tackled successfully with metaheuristic approaches. Several thereof are currently considered state-of-the-art methods for such problems. However, for many years the main focus of research was on the application of single metaheuristics to given problems. A tendency to compare different metaheuristics against each other could be observed, and sometimes this competition led to thinking in stereotypes in the
research communities.
In recent years, it has become evident that the concentration on a sole metaheuristic is rather restrictive, when focusing on the improvement of heuristic techniques to tackle both academic and practical optimization problems. A skilled combination of concepts stemming from different metaheuristics can provide a more efficient behavior and a higher flexibility. Also the hybridization of metaheuristics with other techniques known from classical artificial intelligence areas can be very fruitful. Further, the incorporation of typical operations research techniques can be very beneficial. Combinations of metaheuristic components with components from other metaheuristics or optimization strategies from artificial intelligence or operations research are called hybrid metaheuristics.
The design and implementation of hybrid metaheuristics rises problems going beyond questions about the composition of a single metaheuristic. The proper interaction of
different algorithm components must usually be based on a careful analysis of the single components. Choice and tuning of parameters is more important for the quality of the algorithms than before. Different concepts of interaction at low-level and at high-level are studied. As a result, the design of experiments and the proper statistical evaluation are in a more exposed position than before.
We believe that the combination of elements coming from different metaheuristics, and from classical methods from both artificial intelligence and operations research, bears great chances to become one of the main tracks of research in applied artificial intelligence. It seems to be a promising and rewarding alternative to the still existing mutual contempt between the fields of exact methods and approximate techniques, and also to the competition between the different schools of metaheuristics, which sometimes focused more on a proof of concept than on good general results.
Still, we have to realize that research on hybrid metaheuristics is in main parts based on experimental methods, thus being probably more related to natural sciences than to computer science. It can be stated that both the design and the evaluation of experiments have still not reached the standard as they have in physics or chemistry
for example. The validity of analyses of experimental work on algorithms is a key aspect in hybrid metaheuristics, and the attention of researchers to this aspect seems to be important for the future of the field
Hybrid Metaheuristics: Preface to the proceedings of HM2006
No full textThe International Workshop on Hybrid Metaheuristics reached its third edition with HM 2006. The active and successful participation in the past editions was a clear indication that the research community on metaheuristics and related areas felt the need for a forum to discuss specific aspects of hybridization of metaheuristics. The selection of papers for HM 2006 consolidated some of the mainstream issues that have emerged from the past editions. Firstly, there are prominent examples of effective hybrid techniques whose design and implementation were motivated by challenging real-world applications. A second important issue is that the research community on metaheuristics has become increasingly interested in and open to techniques and methods known from artificial intelligence (AI) and operations research (OR). The awareness of the need for a sound experimental methodology is a third keypoint. This aspect has gained more relevance and currency, even though there are still no widely agreed standard methodologies. As research on hybrid metaheuristics is mostly based on experimental methods, similar standards to those found in the evaluation of experiments in natural sciences can be expected. Scientific testing, a fourth notable aspect, emerges as a fundamental methodology for understanding the behavior of algorithms. The goal of scientific testing is to abstract from actual implementations and study, empirically and through predictive models, the effect of algorithmic components. This research approach can be particularly useful in the case of conjectures on metaheuristic algorithm behavior that, while being widespread in the community, have not yet been the subject of validation. Finally, a tendency to reconsider hybrid metaheuristics from a higher and more general perspective is emerging. Providing classifications, systematic analyses and surveys on important branches underlines a certain maturity of the relatively young field.
For the future, we envision a scenario in which some challenges have to be faced: – It should become common practice that experimental analysis meets high quality standards. This empirical approach is absolutely necessary to produce objective and reproducible results and to anchor the successes of metaheuristics in real-world applications. – Hybrid metaheuristic techniques have to be openly compared not just among themselves but also with state-of-the-art methods, from whatever field they are. By following this approach, researchers would be able to design techniques that meet the goal of solving a real-world problem and to consider the other approaches as rich sources of design components and ideas. – Scientific testing and theoretical models of algorithms for studying their behavior are still confined to a limited area of research. We believe that, by being able to explain rigorously algorithm behavior by means of sound empirical investigation and formal models, researchers would give the field a firmer status and give support to the development of real-world applications. The achievement of these goals will take some time in view of the difficult theoretical and practical problems involved in these challenges. Nevertheless, research is very active and has already produced some remarkable results and studies in this direction
Journal of Mathematical Modelling and Algorithms: Special issue on Hybrid Metaheuristics
No full textCollection of selected and peer reviewed papers on hybrid metaheuristics
Preface to Hybrid Metaheuristics - 6th International Workshop, HM 2009
No full textThe International Workshop on Hybrid Metaheuristics was established with the aim of providing researchers and scholars with a forum for discussing new ideas and research on metaheuristics and their integration with techniques typical of other fields. The papers accepted for the sixth workshop confirm that such a combination is indeed effective and that several research areas can be put together. Slowly but surely, this process has been promoting productive dialogue among researchers with different expertise and eroding barriers between research areas.
The papers in this volume give a representative sample of current research in hybrid metaheuristics. It is worth emphasizing that this year, a large number of papers demonstrated how metaheuristics can be integrated with integer linear programming and other operations research techniques. Constraint programming is also featured, which is a notable representative of artificial intelligence solving methods. Most of these papers are not only a proof of concept – which can be valuable by itself – but also show that the hybrid techniques presented tackle difficult and relevant problems
Hybrid Metaheuristics - 8th International Workshop, HM 2013
Full text linkThe International Workshop on Hybrid Metaheuristics (HM) pursues the
direction of combining application-oriented and fundamental research. This is demonstrated by the papers in the proceedings of this eighth edition of HM. The contributions selected for this volume represent an important sample of current research in hybrid metaheuristics. It is worth emphasizing that the selected papers cover both theoretical and experimental results, including new paradigmatic hybrid solvers, and automatic design approaches as well as applications to logistics and public transport
Hybrid Metaheuristics: An Emerging Approach to Optimization
No full textWhen facing complex and unknown problems, it is very natural to use rules of thumb, common sense, trial and error, so called heuristics in order to find possible answers. Such approaches are at first sight quite different from scientific approaches to a problem, which are usually based on characterizations, deductions, hypotheses and experiments. It is common knowledge that many heuristic criteria and strategies that are used to find good solutions for particular problems share common aspects and are often independent of the problem itself.
In the computer science and artificial intelligence community the term metaheuristic was created and is now well accepted for such general techniques that are not specific to one particular problem. Genetic and evolutionary algorithms, tabu search, simulated annealing, iterated local search, ant colony optimization, scatter search, etc. are typical representatives falling under this generic term. Research in metaheuristics has been very active during the last decades, which is easy to understand when looking at the wide spectrum of fascinating problems that have been successfully tackled and the beauty of the techniques, many of them inspired by nature. Though many combinatorial optimization problems are very hard to solve, it is incredible how good results can be achieved for many instances in practice by rather simple metaheuristic approaches.
These success stories let the researchers also focus on questions why a given metaheuristic is successful, what problem instance characteristics are most informative and which problem model is best for the metaheuristic of choice. Investigations on theoretical aspects began also to be studied and formal theories of some metaheuristics as such were developed. Questions as to which metaheuristic is the best for a given problem were quite common and, more prosaically, often led to a defensive attitude towards other metaheuristics.
It became also evident that the concentration on a sole metaheuristic is rather restrictive for advancing the state of the art when tackling both academic and practical optimization problems. A skilful combination of concepts of different metaheuristics can lead to more efficient behaviour and greater flexibility in many cases. The incorporation of typical operations research (OR) techniques, such as mathematical programming, can be very beneficial, too. Also, the combination of metaheuristics with other techniques known from artificial intelligence (AI), such as constraint programming and data mining, can be very fruitful. Combinations of metaheuristic components with components from other metaheuristics or from AI and OR techniques are called hybrid metaheuristics.
It is somethimes critisized that this unsharp definition does not exactly limit the scope of research in the field. We in contrary believe that this open concepts is a very positive aspect, because in the past indeed too strict boarderlines were often blocking creative research directions. A vivid research community is driven by new ideas and creativity, not by limitations.
In 2004, the editors of this book initiated with the First International Workshop on Hybrid Metaheuristics (HM 2004) a series of annual workshops that has given a forum to researchers who directed their work to integrative approaches that go beyond the borderline of a single metaheuristic. The growing interest in this workshop is an indication that typical questions as to the choice and tuning of parameters, the proper interaction of different algorithm components, the adequate analysis of results etc. do not live any longer in the shadows. With this background, it becomes evident that the field of hybrid metaheuristics clearly belongs to the field of experimental sciences and its strong interdisciplinarity fosters the cooperation among researchers with different expertise.
We feel that it is now time to provide a textbook on hybrid metaheuristics, that collects the most p..
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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