Optimal Scheduling with Nested Time Intervals and Three-Dimensional Strip Packing on Compara-bility Graphs of an Arborescence Order


Book Description

This thesis is concerned with scheduling and three-dimensional packing problems that arise when restricting to nested intervals - either for allocating jobs to time intervals (at machines) or for positioning boxes within a strip. The scheduling problems considered in the first part of this work are motivated by a real-world application in rail car maintenance, and result in a new type of job characteristic introduced into the methodology of scheduling. Being classified as strip packing problems on comparability graphs of an arborescence order, the packing problems of the second part of this thesis are further structurally characterized based on the concept of packing classes. It turns out that using this characterization, these packing problems can equivalently be solved by interval coloring adequate chordal graphs. For several variants of above-mentioned mathematical optimization problems complexity results are derived and approximation, pure heuristical as well as exact solution approaches presented. The performance of the approaches is finally discussed based on computational results.




The Algorithm Design Manual


Book Description

This newly expanded and updated second edition of the best-selling classic continues to take the "mystery" out of designing algorithms, and analyzing their efficacy and efficiency. Expanding on the first edition, the book now serves as the primary textbook of choice for algorithm design courses while maintaining its status as the premier practical reference guide to algorithms for programmers, researchers, and students. The reader-friendly Algorithm Design Manual provides straightforward access to combinatorial algorithms technology, stressing design over analysis. The first part, Techniques, provides accessible instruction on methods for designing and analyzing computer algorithms. The second part, Resources, is intended for browsing and reference, and comprises the catalog of algorithmic resources, implementations and an extensive bibliography. NEW to the second edition: • Doubles the tutorial material and exercises over the first edition • Provides full online support for lecturers, and a completely updated and improved website component with lecture slides, audio and video • Contains a unique catalog identifying the 75 algorithmic problems that arise most often in practice, leading the reader down the right path to solve them • Includes several NEW "war stories" relating experiences from real-world applications • Provides up-to-date links leading to the very best algorithm implementations available in C, C++, and Java




Algorithm Design


Book Description

Algorithm Design introduces algorithms by looking at the real-world problems that motivate them. The book teaches students a range of design and analysis techniques for problems that arise in computing applications. The text encourages an understanding of the algorithm design process and an appreciation of the role of algorithms in the broader field of computer science. The full text downloaded to your computer With eBooks you can: search for key concepts, words and phrases make highlights and notes as you study share your notes with friends eBooks are downloaded to your computer and accessible either offline through the Bookshelf (available as a free download), available online and also via the iPad and Android apps. Upon purchase, you'll gain instant access to this eBook. Time limit The eBooks products do not have an expiry date. You will continue to access your digital ebook products whilst you have your Bookshelf installed.




Meta-Heuristics


Book Description

Meta-Heuristics: Advances and Trends in Local Search Paradigms for Optimizations comprises a carefully refereed selection of extended versions of the best papers presented at the Second Meta-Heuristics Conference (MIC 97). The selected articles describe the most recent developments in theory and applications of meta-heuristics, heuristics for specific problems, and comparative case studies. The book is divided into six parts, grouped mainly by the techniques considered. The extensive first part with twelve papers covers tabu search and its application to a great variety of well-known combinatorial optimization problems (including the resource-constrained project scheduling problem and vehicle routing problems). In the second part we find one paper where tabu search and simulated annealing are investigated comparatively and two papers which consider hybrid methods combining tabu search with genetic algorithms. The third part has four papers on genetic and evolutionary algorithms. Part four arrives at a new paradigm within meta-heuristics. The fifth part studies the behavior of parallel local search algorithms mainly from a tabu search perspective. The final part examines a great variety of additional meta-heuristics topics, including neural networks and variable neighbourhood search as well as guided local search. Furthermore, the integration of meta-heuristics with the branch-and-bound paradigm is investigated.




The Design of Approximation Algorithms


Book Description

Discrete optimization problems are everywhere, from traditional operations research planning problems, such as scheduling, facility location, and network design; to computer science problems in databases; to advertising issues in viral marketing. Yet most such problems are NP-hard. Thus unless P = NP, there are no efficient algorithms to find optimal solutions to such problems. This book shows how to design approximation algorithms: efficient algorithms that find provably near-optimal solutions. The book is organized around central algorithmic techniques for designing approximation algorithms, including greedy and local search algorithms, dynamic programming, linear and semidefinite programming, and randomization. Each chapter in the first part of the book is devoted to a single algorithmic technique, which is then applied to several different problems. The second part revisits the techniques but offers more sophisticated treatments of them. The book also covers methods for proving that optimization problems are hard to approximate. Designed as a textbook for graduate-level algorithms courses, the book will also serve as a reference for researchers interested in the heuristic solution of discrete optimization problems.




Handbook on Modelling for Discrete Optimization


Book Description

This book aims to demonstrate and detail the pervasive nature of Discrete Optimization. The handbook couples the difficult, critical-thinking aspects of mathematical modeling with the hot area of discrete optimization. It is done with an academic treatment outlining the state-of-the-art for researchers across the domains of the Computer Science, Math Programming, Applied Mathematics, Engineering, and Operations Research. The book utilizes the tools of mathematical modeling, optimization, and integer programming to solve a broad range of modern problems.




Materials Management


Book Description

This book examines the problem of managing the flow of materials into, through, and out of a system in order to improve the efficiency and effectiveness of materials management. The subject is crucial for global competitive advantage, as materials constitute the largest single cost factor in manufacturing and service, and their effective management enhances value for money. In this context, inventory is a barometer of materials management effectiveness, along with wastage of materials. The book adopts a comprehensive, integrated systems approach and covers almost all aspects of materials, considering the specification, procurement, storage, handling, issue, use and accounting of materials to get the most out of every dollar invested. Combining conceptual clarity and quantitative rigor, it will be a highly useful guide for practicing managers, academics and researchers in this vital functional area.







Statistical Models for Strategic Management


Book Description

Statistical Models for Strategic Management offers practical guidance in the use of statistical models for empirical research in strategic management. The contributions in this edited volume come from distinguished researchers in the field of Strategic Management, and provide illustration of most statistical models that are relevant for strategy research. The book is divided into four major topical areas: Strategic Analysis and Firm Strategies; The Resource-Based View of the Firm; Transaction Costs, Agency Theory, and the Boundaries of the Firm; and Corporate Alliances, Acquisitions and Networks.




Approximation Algorithms


Book Description

Covering the basic techniques used in the latest research work, the author consolidates progress made so far, including some very recent and promising results, and conveys the beauty and excitement of work in the field. He gives clear, lucid explanations of key results and ideas, with intuitive proofs, and provides critical examples and numerous illustrations to help elucidate the algorithms. Many of the results presented have been simplified and new insights provided. Of interest to theoretical computer scientists, operations researchers, and discrete mathematicians.