Andreas Fink – författare

This book includes a selection of refereed papers presented at the "Annual International Conference of the German Operations Research Society (OR2016)," which took place at the Helmut-Schmidt-Universität / Universität der Bundeswehr Hamburg, Germany, Aug. 30 - Sept.

Logistics and supply chain management deal with managing the ?ow of goods or services within a company, from suppliers to customers, and along a supply chain where companies act as suppliers as well as customers. As transportation is at the heart of logistics, the design of tra?c and transportation networks combined with the routing of vehicles and goods on the networks are important and demanding planning tasks. The in?uence of transport, logistics, and s- ply chain management on the modern economy and society has been growing steadily over the last few decades. The worldwide division of labor, the conn- tion of distributed production centers, and the increased mobility of individuals lead to an increased demand for e?cient solutions to logistics and supply chain management problems. On the company level, e?cient and e?ective logistics and supply chain management are of critical importance for a company’s s- cessanditscompetitiveadvantage. Properperformanceofthelogisticsfunctions can contribute both to lower costs and to enhanced customer service. Computational Intelligence (CI) describes a set of methods and tools that often mimic biological or physical principles to solve problems that have been di?cult to solve by classical mathematics. CI embodies neural networks, fuzzy logic, evolutionary computation, local search, and machine learning approaches. Researchersthat workinthis areaoften comefromcomputer science,operations research,or mathematics, as well as from many di?erent engineering disciplines. Popular and successful CI methods for optimization and planning problems are heuristic optimization approaches such as evolutionary algorithms, local search methods, and other types of guided search methods.

This book constitutes the refereed joint proceedings of seven workshops on evolutionary computing, EvoWorkshops 2007, held in Valencia, Spain in April 2007. It examines evolutionary computation in communications, networks, and connected systems; finance and economics; image analysis and signal processing; and transportation and logistics. Coverage also details evolutionary algorithms in stochastic and dynamic environments.

Evolutionary computation (EC) techniques are e?cient, nature-inspired pl- ning and optimization methods based on the principles of natural evolution and genetics. Due to their e?ciency and simple underlying principles, these me- ods can be used in the context of problem solving, optimization, and machine learning. A large and continuously increasing number of researchers and prof- sionals make use of EC techniques in various application domains. This volume presents a careful selection of relevant EC examples combined with a thorough examination of the techniques used in EC. The papers in the volume illustrate the current state of the art in the application of EC and should help and - spire researchers and professionals to develop e?cient EC methods for design and problem solving. All papers in this book were presented during EvoWorkshops 2008, which consisted of a range of workshops on application-oriented aspects of EC. Since 1998, EvoWorkshops has provided a unique opportunity for EC researchers to meet and discuss applicationaspectsofECandhasservedasanimportantlink between EC research and its application in a variety of domains. During these ten years new workshops have arisen, some have disappeared, while others have matured to become conferences of their own, such as EuroGP in 2000, EvoCOP in 2004, and EvoBIO last year.

Data Analysis, Data Handling and Business Intelligence are research areas at the intersection of computer science, artificial intelligence, mathematics, and statistics. They cover general methods and techniques that can be applied to a vast set of applications such as in marketing, finance, economics, engineering, linguistics, archaeology, musicology, medical science, and biology. This volume contains the revised versions of selected papers presented during the 32nd Annual Conference of the German Classification Society (Gesellschaft für Klassifikation, GfKl). The conference, which was organized in cooperation with the British Classification Society (BCS) and the Dutch/Flemish Classification Society (VOC), was hosted by Helmut-Schmidt-University, Hamburg, Germany, in July 2008.

The year 2009 celebrates the bicentenary of Darwin’s birth and the 150th - niversary of the publication of his seminal work, On the Origin of Species.If this makes 2009 a special year for the research community working in biology and evolution, the ?eld of evolutionary computation (EC) also shares the same excitement. EC techniques are e?cient, nature-inspired planning and optimi- tion methods based on the principles of natural evolution and genetics. Due to their e?ciency and simple underlying principles, these methods can be used in the context of problem solving, optimization, and machine learning. A large and ever-increasing number of researchers and professionals make use of EC te- niques in various application domains. ThisvolumepresentsacarefulselectionofrelevantECapplicationscombined with a thorough examination of the techniques used in EC. The papers in the volume illustrate the current state of the art in the application of EC and can help and inspire researchers and professionals to develop e?cient EC methods for design and problem solving.

Logistics and supply chain management deal with managing the ?ow of goods or services within a company, from suppliers to customers, and along a supply chain where companies act as suppliers as well as customers. As transportation is at the heart of logistics, the design of tra?c and transportation networks combined with the routing of vehicles and goods on the networks are important and demanding planning tasks. The in?uence of transport, logistics, and s- ply chain management on the modern economy and society has been growing steadily over the last few decades. The worldwide division of labor, the conn- tion of distributed production centers, and the increased mobility of individuals lead to an increased demand for e?cient solutions to logistics and supply chain management problems. On the company level, e?cient and e?ective logistics and supply chain management are of critical importance for a company’s s- cessanditscompetitiveadvantage. Properperformanceofthelogisticsfunctions can contribute both to lower costs and to enhanced customer service. Computational Intelligence (CI) describes a set of methods and tools that often mimic biological or physical principles to solve problems that have been di?cult to solve by classical mathematics. CI embodies neural networks, fuzzy logic, evolutionary computation, local search, and machine learning approaches. Researchersthat workinthis areaoften comefromcomputer science,operations research,or mathematics, as well as from many di?erent engineering disciplines. Popular and successful CI methods for optimization and planning problems are heuristic optimization approaches such as evolutionary algorithms, local search methods, and other types of guided search methods.

Evolutionary computation (EC) techniques are e?cient, nature-inspired me- ods based on the principles of natural evolution and genetics. Due to their - ciency and simple underlying principles, these methods can be used for a diverse rangeofactivitiesincludingproblemsolving,optimization,machinelearningand pattern recognition. A large and continuously increasing number of researchers and professionals make use of EC techniques in various application domains. This volume presents a careful selection of relevant EC examples combined with a thorough examination of the techniques used in EC. The papers in the volume illustrate the current state of the art in the application of EC and should help and inspire researchers and professionals to develop e?cient EC methods for design and problem solving. All papers in this book were presented during EvoApplications 2010, which included a range of events on application-oriented aspects of EC. Since 1998, EvoApplications — formerly known as EvoWorkshops — has provided a unique opportunity for EC researchers to meet and discuss application aspects of EC and has been an important link between EC research and its application in a variety of domains. During these 12 years, new events have arisen, some have disappeared,whileothershavematuredtobecomeconferencesoftheirown,such as EuroGP in 2000, EvoCOP in 2004, and EvoBIO in 2007. And from this year, EvoApplications has become a conference as well.