Inernational workshop on Hybrid metaheuristics - HM2004

Workshop on Hybrid metaheuristics, held as a satellite event of ECAI 2004 - Valencia, August 200

Hybrid Metaheuristics: Editorial to the special issue

Combinations of metaheuristic components with components from other metaheuristics or optimization strategies from AI and OR are called hybrid metaheuristics. The design and implementation of hybrid metaheuristics raises problems going beyond questions about the design of a single metaheuristic. Choice and tuning of parameters is for example rendered more difficult by the problem of how to achieve a proper interaction of different algorithm components. Interaction can take place at low-level, using functions from different metaheuristics, or at high-level, e.g., using a portfolio of metaheuristics for automated hybridization. This special issue of the Journal of Mathematical Modelling and Algorithms is devoted to this interdisciplinary topic and contains six papers covering a wide spectrum of subjects

Random walk and parallelism in local search

The use of randomness in local search is a widespread technique applied to improve algorithm performance. A property of noise strategies, i.e., strategies that make use of randomness, is that there is an optimal amount of randomness that enables the algorithm to achieve on optimal performance. The same property holds also for another technique introduced in local search, that is the parallel application of more than one local move. In this work, we investigate the outcome of the combination of both the techniques. We show that in the case of random 3-SAT instances a synergistic effect comes into play and the resulting technique outperforms the single ones

Combining ILS with an effective constructive heuristic for the application to error correcting code design

Error correcting code (ECC) design is a hard optimization problem arising in telecommunication applications. In the electronic transmission of messages it often happens—due to noisy channels—that the arriving message is corrupted. One solution to this problem consists in transmitting the message several times in order to increase the probability of its safe arrival. However, this is often too costly. Instead, it is nowadays standard to use ECC. In this paper we focus on the design of linear block codes. In particular, we want to find the best possible code for a given number of code-words M with a given length n, i.e., a code where the minimum Hamming distance d between code-words is as big as possible. For this purpose we propose an iterated local search algorithm that uses a particular constructive heuristic for generating the initial solution. The experimental results show that our algorithm is currently a state-of-the-art method for the ECC problem

Hybrid Metaheuristics

The hybridization with other techniques for optimization has been one of the most interesting recent trends for what concerns research on metaheuristics. In fact, the focus of research on metaheuristics has notably shifted from an algorithm-oriented point of view to a problem-oriented point of view. In other words, in contrast to promoting a certain metaheuristic, as, for example, in the eighties and the first half of the nineties, nowadays researchers focus much more on solving, as best as possible, the problem at hand. This has inevitably led to research that aims at combining different algorithmic components for the design of algorithms that are more powerful than the ones resulting from the implementation of pure metaheuristic strategies. Interestingly, the trend of hybridization is not restricted to the combination of algorithmic components originating from different metaheuristics, but has also been extended to the combination of exact algorithms and metaheuristics. In this chapter we provide an overview of the most important lines of hybridization. In addition to representative examples we present a literature review for each of the considered hybridization types

Preface to Hybrid Metaheuristics - 7th International Workshop, HM 2010

Research in hybrid metaheuristics is now established as a reference field in the areas of optimization and problem solving. Hybrid metaheuristics have a strong impact on applications because they provide efficient and powerful problem solving techniques for optimization problems in industry. Furthermore, the related interdisciplinary research community provides a fertile environment where innovative techniques are presented and discussed. The International Workshop on Hybrid Metaheuristics pursues the direction of combining application-oriented and foundational research. This is demonstrated by the papers in the proceedings of this 7th HM event. 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 applicational results, including applications to logistics and bioinformatics and new paradigmatic hybrid solvers

Hybrid Metaheuristics: Preface to the proceedings of HM2007

The International Workshop on Hybrid Metaheuristics is now an established event and reaches its fourth edition with HM 2007. One of the main motivations for initiating it was the need for a forum to discuss specific aspects of hybridiza- tion of metaheuristics. Hybrid metaheuristics design, development and testing require a combination of skills and a sound methodology. In particular, com- parisons among hybrid techniques and assessment of their performance have to be supported by a sound experimental methodology, and one of the mainstream issues of the workshop is to promote agreed standard experimental methodolo- gies. These motivations are still among the driving forces behind the workshop and, in these four years, we have observed an increasing attention to methodolog- ical aspects, from both the empirical and theoretical sides. The papers selected for presentation at HM 2007 are indeed a representative sample of research in the field of hybrid metaheuristics. They range from methodological to applica- tion papers. Moreover, some of them put special emphasis on the experimental analysis and statistical assessment of results

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

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

Enumeration of 166 Billion Organic Small Molecules in the Chemical Universe Database GDB-17

Drug, molecules consist of a few tens of atoms connected by covalent bonds. Haw many such molecules are possible in total and what is their structure? This question is of pressing interest in: medicinal. chemistry to help solve the problems of drug potency, selectivity, and toxicity and reduce attrition rates by pointing to new molecular series. To better define the unknown chemical space, we have enumerated 166.4 billion molecules of up to 17 atoms of C, N, O, S, and halogens forming the Chemical-universe. database GDB-17, covering a size range containing many drugs and typical for lead compounds. GDB-17 contains Millions of isomers of known drugs,. including analogs: with high, shape : similarity to the parent drug. Compared to known molecules in PubChem, GDB-17 molecules are much richer in nonaromatic hetero- cycles, quaternary centers, and stereoisomers, densely populate the third dimension in shape space and represent many more scaffold types

Preface to HM 2008 -- Fifth International Workshop on Hybrid Metaheuristics

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\u2019s 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