A First Course in Combinatorial Optimization is a text for a one-semester introductory graduate-level course for students of operations research, mathematics, and computer science. It is a self-contained treatment of the subject, requiring only some mathematical maturity. Topics include: linear and integer programming, polytopes, matroids and matroid optimization, shortest paths, and network flows. Central to the exposition is the polyhedral viewpoint, which is the key principle underlying the successful integer-programming approach to combinatorial-optimization problems. Another key unifying topic is matroids. The author does not dwell on data structures and implementation details, preferring to focus on the key mathematical ideas that lead to useful models and algorithms. Problems and exercises are included throughout as well as references for further study.
This volume contains the proceedings of the workshop on Optimization Theory and Related Topics, held in memory of Dan Butnariu, from January 11-14, 2010, in Haifa, Israel. An active researcher in various fields of applied mathematics, Butnariu published over 80 papers. His extensive bibliography is included in this volume. The articles in this volume cover many different areas of Optimization Theory and its applications: maximal monotone operators, sensitivity estimates via Lyapunov functions, inverse Newton transforms, infinite-horizon Pontryagin principles, singular optimal control problems with state delays, descent methods for mixed variational inequalities, games on MV-algebras, ergodic convergence in subgradient optimization, applications to economics and technology planning, the exact penalty property in constrained optimization, nonsmooth inverse problems, Bregman distances, retraction methods in Banach spaces, and iterative methods for solving equilibrium problems. This volume will be of interest to both graduate students and research mathematicians.
A metaheuristic is a set of concepts that can be used to define heuristic methods that can be applied to a wide set of different problems. This volume presents a family of advanced methods of optimization called metaheuristics. This category covers simulated annealing, tabu search, evolutionary and genetic algorithms, and ant colonies. The book contains various case studies from engineering and operations research, and includes commented literature for each chapter.
Grounded Theory (GT) has been used extensively in management, organizational studies and 'caring professions' such as in psychology, education and the medical profession. But outside these areas, GT is often mistakenly associated with qualitative research traditions such as action research or ethnography. This book demystifies GT for language teachers and researchers. Issues related to epistemology and similar qualitative methodologies will be addressed in order to dispel some of the misconceptions of GT in the TESOL community. Real life examples of how GT is used in the field will help to illustrate a number of opportunities and challenges that are frequently encountered. A distinguishing feature of this book is the linking of GT to ways in which it can generate deeper insight and suggest new ways to address issues in the classrooms and institutions of language teachers. Issues related to disseminating findings, ethical considerations and potential future developments of GT will also be discussed.
Synthesis and Optimization of DSP Algorithms describes approaches taken to synthesising structural hardware descriptions of digital circuits from high-level descriptions of Digital Signal Processing (DSP) algorithms. The book contains:
-A tutorial on the subjects of digital design and architectural synthesis, intended for DSP engineers,
Synthesis and Optimization of DSP Algorithms is of use both to researchers and students in the field of design automation for DSP systems, and to those wishing to implement state-of-the-art techniques within an Electronic Design Automation framework.