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Book Description
Generalized network design is a very hot topic of research. The monograph describes in a unified manner a series of mathematical models, methods, propositions, and algorithms developed in the last years on generalized network design problems. The book consists of seven chapters, where in addition to an introductory chapter, a number of six generalized network design problems are formulated and examined. The book will be useful for researchers and graduate students interested in operations research, optimization, applied mathematics, and computer science. Due to the substantial practical importance of some presented problems, researchers in other areas will also find it useful.

Book Description
Generalized network design is a very hot topic of research. The monograph describes in a unified manner a series of mathematical models, methods, propositions, and algorithms developed in the last years on generalized network design problems. The book consists of seven chapters, where in addition to an introductory chapter, a number of six generalized network design problems are formulated and examined. The book will be useful for researchers and graduate students interested in operations research, optimization, applied mathematics, and computer science. Due to the substantial practical importance of some presented problems, researchers in other areas will also find it useful.

Book Description
In this book, we consider several generalized network design problems which belong to the family of NP-hard combinatorial optimization problems. In contrast to their classical counterparts, the generalized versions are defined on graphs whose node sets are partitioned into clusters. The goal is to find a subgraph which spans exactly one node from each cluster and also meets further constraints respectively. Applicable methodologies for solving combinatorial optimization problems can roughly be divided into two mainstreams. The first class consists of algorithms which aim to solve these problems to proven optimality - provided that they are given enough run-time and memory. The second class are metaheuristics which compute approximate solutions but usually require significantly less run-time. By combining these two classes, we are able to form collaboration algorithms that benefit from advantages of both sides. Such approaches are considered for solving the generalized network design problems in this book.

Book Description
The goal of the Encyclopedia of Optimization is to introduce the reader to a complete set of topics that show the spectrum of research, the richness of ideas, and the breadth of applications that has come from this field. The second edition builds on the success of the former edition with more than 150 completely new entries, designed to ensure that the reference addresses recent areas where optimization theories and techniques have advanced. Particularly heavy attention resulted in health science and transportation, with entries such as "Algorithms for Genomics", "Optimization and Radiotherapy Treatment Design", and "Crew Scheduling".

Book Description
This thesis is concerned with mathematical optimization under data uncertainty using mixed integer linear programming (MILP) techniques. Our investigations follow the deterministic paradigm known as robust optimization. It allows to tackle an uncertain variant of a problem without increasing its complexity in theory or decreasing its computational tractability in practice. We consider four robustness concepts for robust optimization and describe their parametrization, application, and evaluation. The concepts are Γ-robustness, its generalization multi-band robustness, the more general submodular robustness, and the two-staged adaptive approach called recoverable robustness. For each concept, we investigate the corresponding robust generalization of the knapsack problem (KP), a fundamental combinatorial problem and subproblem of almost every integer linear programming (ILP) problem, and many other optimization problems. We present ILP formulations, detailed polyhedral investigations including new classes of valid inequalities, and algorithms for each robust KP. In particular, our results for the submodular and recoverable robust KP are novel. Additionally, the recoverable robust KP is experimentally evaluated in detail. Further, we consider the Γ-robust generalization of the capacitated network design problem (NDP). For example, the NDP arises from many application areas such as telecommunications, transportation, or logistics. We present MILP formulations, detailed polyhedral insights with new classes of valid inequalities, and algorithms for the Γ-robustness NDP. Moreover, we consider the multi-band robust NDP, its MILP formulations, and generalized polyhedral results of the Γ- robustness NDP. Finally, we present computational results for the Γ-robustness NDP using real-world measured uncertain data from telecommunication networks. These detailed representative studies are based on our work with the German ROBUKOM project in cooperation with Partner Nokia Siemens Networks GmbH & Co. KG. Die vorliegende Dissertation untersucht mathematische Optimierung unter Unsicherheiten mittels Methoden der gemischt-ganzzahligen linearen Programmierung (MILP). Dabei folgen wir dem deterministischen Paradigma der robusten Optimierung. Dieses ermöglicht die Lösung unsicherer Problemvarianten ohne Erhöhung der theoretischen Komplexität oder Verschlechterung der praktischen Lösbarkeit. Wir untersuchen vier Robustheitskonzepte und beschreiben deren Parametrisierung, Anwendung, und Evaluierung. Die untersuchten Konzepte sind Γ-Robustheit (engl. Γ-robustness), deren neue Verallgemeinerung Multi-Band-Robustheit (engl. multi-band robustness), die neue allgemeinere submodulare Robustheit (engl. submodular robustness), sowie der adaptive zweistufige Ansatz der wiederherstellbaren Robustheit (engl. recoverable robustness) Für jedes Konzept untersuchen wir die entsprechende robuste Verallgemeinerung des Rucksackproblems (engl. knapsack problem) (KP), eines der fundamentalen kombinatorischen Probleme und Teilproblem fast jeden Problems der ganzzahligen linearen Programmierung (ILP) und vieler anderer Optimierungsprobleme. Wir präsentieren ILP-Formulierungen, detaillierte polyedrische Studien mit neuen Klassen gültiger Ungleichungen und Algorithmen für jedes robuste KP. Dabei sind insbesondere unsere Ergebnisse für das submodular- und wiederherstellbar-robuste KP neuartig. Zusätzlich evaluieren wir das wiederherstellbar- robuste KP experimentell in einer detaillierten Rechenstudie. Außerdem betrachten wir die Γ-robuste Verallgemeinerung des kapazitierten Netzwerkplanungsproblems (engl. capacitated network design problem) (NDP). Das NDP ist z. B. in Anwendungsproblemen aus den Bereichen Telekommunikation, Transport oder Logistik zu finden. Für das Γ-robuste NDP präsentieren wir MILP-Formulierungen, detaillierte polyedrische Ergebnisse, neue Klassen gültiger Ungleichungen und Algorithmen. Zusätzlich untersuchen wir das Multi-Band-robuste NDP, dessen MILP-Formulierungen, sowie dessen polyedrische Struktur als Verallgemeinerung des Γ-robusten NDP. Abschließend präsentieren wir detaillierten Rechenstudien zum Γ-robusten NDP mit real gemessenen unsicheren Daten verschiedener Telekommunikationsnetze. Diese repräsentativen Rechenergebnisse basieren auf unserer Arbeit im Projekt ROBUKOM in Kooperation mit Nokia Siemens Networks GmbH & Co. KG.

Book Description
"Combinatorial optimization is a fascinating topic. Combinatorial optimization problems arise in a wide variety of important fields such as transportation, telecommunications, computer networking, location, planning, distribution problems, etc. Important and significant results have been obtained on the theory, algorithms and applications over the last few decades. In combinatorial optimization, many network design problems can be generalized in a natural way by considering a related problem on a clustered graph, where the original problem's feasibility constraints are expressed in terms of the clusters, i.e., node sets instead of individual nodes. This class of problems is usually referred to as generalized network design problems (GNDPs) or generalized combinatorial optimization problems. The express purpose of this monograph is to describe a series of mathematical models, methods, propositions, algorithms developed in the last years on generalized network design problems in a unified manner. The book consists of seven chapters, where in addition to an introductory chapter, the following generalized network design problems are formulated and examined: the generalized minimum spanning tree problem, the generalized traveling salesman problem, the railway traveling salesman problem, the generalized vehicle routing problem, the generalized fixed-charge network design problem and the generalized minimum vertex-biconnected network problem. The book will be useful for researchers, practitioners, and graduate students in operations research, optimization, applied mathematics and computer science. Due to the substantial practical importance of some presented problems, researchers in other areas will find this book useful, too."--Publisher's website.

Book Description
This volume constitutes the proceedings of the 9th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2014, held in Salamanca, Spain, in June 2014. The 61 papers published in this volume were carefully reviewed and selected from 199 submissions. They are organized in topical sessions on HAIS applications; data mining and knowledge discovery; video and image analysis; bio-inspired models and evolutionary computation; learning algorithms; hybrid intelligent systems for data mining and applications and classification and cluster analysis.

Book Description
This book of Springer Nature is another proof of Springer’s outstanding and greatness on the lively interface of Smart Computational Optimization, Green ICT, Smart Intelligence and Machine Learning! It is a Master Piece of what our community of academics and experts can provide when an Interconnected Approach of Joint, Mutual and Meta Learning is supported by Modern Operational Research and Experience of the World-Leader Springer Nature! The 5th edition of International Conference on Intelligent Computing and Optimization took place at October 27–28, 2022, via Zoom. Objective was to celebrate “Creativity with Compassion and Wisdom” with researchers, scholars, experts and investigators in Intelligent Computing and Optimization across the planet, to share knowledge, experience, innovation—a marvelous opportunity for discourse and mutuality by novel research, invention and creativity. This proceedings book of ICO’2022 is published by Springer Nature—Quality Label of wonderful.

Book Description
This book explores the methodological and application developments of network design in transportation and logistics. It identifies trends, challenges and research perspectives in network design for these areas. Network design is a major class of problems in operations research where network flow, combinatorial and mixed integer optimization meet. The analysis and planning of transportation and logistics systems continues to be one of the most important application areas of operations research. Networks provide the natural way of depicting such systems, so the optimal design and operation of networks is the main methodological area of operations research that is used for the analysis and planning of these systems. This book defines the current state of the art in the general area of network design, and then turns to its applications to transportation and logistics. New research challenges are addressed. Network Design with Applications to Transportation and Logistics is divided into three parts. Part I examines basic design problems including fixed-cost network design and parallel algorithms. After addressing the basics, Part II focuses on more advanced models. Chapters cover topics such as multi-facility network design, flow-constrained network design, and robust network design. Finally Part III is dedicated entirely to the potential application areas for network design. These areas range from rail networks, to city logistics, to energy transport. All of the chapters are written by leading researchers in the field, which should appeal to analysts and planners.

Book Description
The two-volume set LNCS 8111 and LNCS 8112 constitute the papers presented at the 14th International Conference on Computer Aided Systems Theory, EUROCAST 2013, held in February 2013 in Las Palmas de Gran Canaria, Spain. The total of 131 papers presented were carefully reviewed and selected for inclusion in the books. The contributions are organized in topical sections on modelling biological systems; systems theory and applications; intelligent information processing; theory and applications of metaheuristic algorithms; model-based system design, verification and simulation; process modeling simulation and system optimization; mobile and autonomous transportation systems; computer vision, sensing, image processing and medical applications; computer-based methods and virtual reality for clinical and academic medicine; digital signal processing methods and applications; mechatronic systems, robotics and marine robots; mobile computing platforms and technologies; systems applications.

Book Description
This book surveys state-of-the-art optimization modeling for design, analysis, and management of wireless networks, such as cellular and wireless local area networks (LANs), and the services they deliver. The past two decades have seen a tremendous growth in the deployment and use of wireless networks. The current-generation wireless systems can provide mobile users with high-speed data services at rates substantially higher than those of the previous generation. As a result, the demand for mobile information services with high reliability, fast response times, and ubiquitous connectivity continues to increase rapidly. The optimization of system performance has become critically important both in terms of practical utility and commercial viability, and presents a rich area for research. In the editors' previous work on traditional wired networks, we have observed that designing low cost, survivable telecommunication networks involves extremely complicated processes. Commercial products available to help with this task typically have been based on simulation and/or proprietary heuristics. As demonstrated in this book, however, mathematical programming deserves a prominent place in the designer's toolkit. Convenient modeling languages and powerful optimization solvers have greatly facilitated the implementation of mathematical programming theory into the practice of commercial network design. These points are equally relevant and applicable in today’s world of wireless network technology and design. But there are new issues as well: many wireless network design decisions, such as routing and facility/element location, must be dealt with in innovative ways that are unique and distinct from wired (fiber optic) networks. The book specifically treats the recent research and the use of modeling languages and network optimization techniques that are playing particularly important and distinctive roles in the wireless domain.