Andrea Roli – författare

This book constitutes the revised selected papers of the 13th Italian Workshop on Artificial Life and Evolutionary Computation, WIVACE 2018, held in Parma, Italy, in September 2018.The 12 full papers presented were thoroughly reviewed and selected from 30 submissions. They cover the following topics: Boolean networks and complex systems; economic, societal and technological applications; chemical, biological and medical applications.The chapter “Unveiling Latent Relations in the Photonics Techno-Economic Complex System” is open access under a CC BY 4.0 license at link.springer.com.

This book constitutes the revised selected papers of the 12th Italian Workshop on Advances in Artificial Life, Evolutionary Computation, WIVACE 2017, held in Venice, Italy, in September 2017.The 23 full papers presented were thoroughly reviewed and selected from 33 submissions. They cover the following topics: physical-chemical phenomena; biological systems; economy and society; complexity; optimization.

Combinatorial optimization and in particular the great variety of fascinating problemsthatbelong to thisareahaveattractedmanyresearchersformorethan halfacentury.Duetothepracticalrelevanceofsolvinghardreal-worldproblems, much research e?ort has been devoted to the development of heuristic methods aimed at ?nding good approximate solutions in a reasonable computation time. Some solution paradigms that are not speci?c for one particular problem have been deeply studied in the past, and the term metaheuristic is now common for such optimization heuristics. Several metaheuristics - simulated annealing, - netic and evolutionary algorithms, tabu search, ant colony optimization, scatter search, iterated local search, and greedy randomized adaptive search procedures beingsomeofthem-havefoundtheirownresearchcommunities,andspecialized conferences devoted to such techniques have been organized. Plenty of classical hard problems, such as the quadratic assignment pr- lem, the traveling salesman problem, problems in vehicle routing, scheduling, and timetabling, etc., have been tackled successfully with metaheuristic - proaches.Several thereof are currently considered state-of-the-art methods for solving 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 di?erent metaheuristics against each other could be observed, and sometimes this competition led to thinking in stereotypes in the research communities.

The 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 speci?c 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 e?ective hybrid techniques whose design and implementation were motivated by challenging real-world applications. We believe this is particularly important for two reasons: on the one hand, researchers are conscious that the primary goal of developing algorithms is to solve relevant real-life problems; on the other hand, the path towarde?cient solving methods for practical problems is a source of new outstanding ideas and theories. A second important issue is that the research community on metaheur- tics has become increasingly interested in and open to techniques and methods known from arti?cial intelligence (AI) and operations research (OR). So far, the most representative examples of such integration have been the use of AI/OR techniques as subordinates of metaheuristic methods. As a historical and - ymological note, this is in perfect accordance with the original meaning of a metaheuristic as a “general strategy controlling a subordinate heuristic. ” The awareness of the need for a sound experimental methodology is a third keypoint.

This book constitutes the refereed proceedings of the 4th International Workshop on Hybrid Metaheuristics, HM 2007, held in Dortmund, Germany. The 14 revised full papers discuss specific aspects of hybridization of metaheuristics, hybrid metaheuristics design, development and testing. With increasing attention to methodological aspects, from both the empirical and theoretical sides, the papers show a representative sample of research in the field of hybrid metaheuristics.

Optimization problems are of great importance in many fields. They can be tackled, for example, by approximate algorithms such as metaheuristics. Examples of metaheuristics are simulated annealing, tabu search, evolutionary computation, iterated local search, variable neighborhood search, and ant colony optimization. In recent years it has become evident that a skilled combination of a metaheuristic with other optimization techniques, a so called hybrid metaheuristic, can provide a more efficient behavior and a higher flexibility. This is because hybrid metaheuristics combine their advantages with the complementary strengths of, for example, more classical optimization techniques such as branch and bound or dynamic programming.The authors involved in this book are among the top researchers in their domain. The book is intended both to provide an overview of hybrid metaheuristics to novices of the field, and to provide researchers from the field with a collection of some of the most interesting recent developments.

This book constitutes the refereed proceedings of the 5th International Workshop on Hybrid Metaheuristics, HM 2008, held in Malaga, Spain, in October 2008. The 14 revised full papers presented were carefully reviewed and selected from 33 submissions. The papers discuss specific aspects of combinations of metaheuristics and other solving techniques for tackling particular relevant constrained optimization problems, such as fiber optic networks, time tabling and freight train scheduling problems.

The 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 ?elds. The papers accepted for the sixth workshop con?rm that such a combination is indeed e?ective and that several research areas can be put together.Slowlybut surely,thisprocesshasbeen promotingproductivedialogue amongresearcherswithdi?erentexpertiseanderodingbarriersbetweenresearch areas. The papers in this volume give a representativesample of current researchin hybrid metaheuristics. It is worth emphasizing that this year, a large number of papers demonstrated how metaheuristics can be integrated with integer linear programmingandotheroperationsresearchtechniques.Constraintprogramming is also featured, which is a notable representative of arti?cial 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 di?cult and relevant problems. In keeping with the tradition of this workshop, special care was exercised in the review process: out of 22 submissions received, 12 papers were selected on the basis of reviews by the Program Committee members and evaluations by the Program Chairs. Reviews were in great depth: reviewers sought to p- vide authors with constructive suggestions for improvement. Special thanks are extended to the Program Committee members who devoted their time and - fort. Special gratitude is due to Andrea Lodi and Vittorio Maniezzo, who both accepted our invitation to give an overview talk.

Optimization problems are of great importance in many fields. They can be tackled, for example, by approximate algorithms such as metaheuristics. Examples of metaheuristics are simulated annealing, tabu search, evolutionary computation, iterated local search, variable neighborhood search, and ant colony optimization. In recent years it has become evident that a skilled combination of a metaheuristic with other optimization techniques, a so called hybrid metaheuristic, can provide a more efficient behavior and a higher flexibility. This is because hybrid metaheuristics combine their advantages with the complementary strengths of, for example, more classical optimization techniques such as branch and bound or dynamic programming.The authors involved in this book are among the top researchers in their domain. The book is intended both to provide an overview of hybrid metaheuristics to novices of the field, and to provide researchers from the field with a collection of some of the most interesting recent developments.

Research in hybrid metaheuristics is now established as a reference ?eld in the areas of optimization and problem solving. Hybrid metaheuristics have a strong impactonapplicationsbecausethey providee?cientandpowerfulproblemso- ing techniques for optimization problems in industry. Furthermore, the related interdisciplinary research community provides a fertile environment where in- vative techniques are presented and discussed. The International Workshop on Hybrid Metaheuristics pursues the direction of combining application-oriented and foundational research. This is dem- strated by the papers in the proceedings of this 7th HM event. The contri- tions selected for this volume represent an important sample of current research in hybrid metaheuristics. It is worth emphasizing that the selected papers cover both theoreticaland applicational results,including applications to logistics and bioinformatics and new paradigmatic hybrid solvers. As is the tradition of the workshop, special care was exercised in the review process: out of 29 submissions received, 14 papers were selected on the basis of the reviews and evaluations provided by the Program Committee and Program Chair members.Reviews were detailed and reviewers provided authors with constructive suggestions for improving their work. Special thanks are extended to the Program Committee members who devoted their e?ort and time to this service. We believe that this selection of papers will be of interest to researchers and scholars working in the area of optimization and problem solving. Moreover, we hope that, by showing the success of ideas generated from connections - tween two di?erent research ?elds, we can stimulate cross-fertilization between computer science and engineering.