This book presents a radically new approach to problems of evaluating and optimizing the performance of continuous-time stochastic systems. This approach is based on the use of a family of Markov processes called Piecewise-Deterministic Processes (PDPs) as a general class of stochastic system models. A PDP is a Markov process that follows deterministic trajectories between random jumps, the latter occurring either spontaneously, in a Poisson-like fashion, or when the process hits the boundary of its state space. This formulation includes an enormous variety of applied problems in engineering, operations research, management science and economics as special cases; examples include queueing systems, stochastic scheduling, inventory control, resource allocation problems, optimal planning of production or exploitation of renewable or non-renewable resources, insurance analysis, fault detection in process systems, and tracking of maneuvering targets, among many others.
This book deals with combinatorial aspects of epistasis, a notion that existed for years in genetics and appeared in the ?eld of evolutionary algorithms in the early 1990s. Even thoughthe?rst chapterputsepistasisintheperspective ofevolutionary algorithms and arti?cial intelligence, and applications occasionally pop up in other chapters, thisbookisessentiallyaboutmathematics, aboutcombinatorialtechniques to compute in an e?cient and mathematically elegant way what will be de?ned as normalized epistasis. Some of the material in this book ?nds its origin in the PhD theses of Hugo Van Hove  and Dominique Suys . The sixth chapter also contains material that appeared in the dissertation of Luk Schoofs . Together with that of M. Teresa Iglesias , these dissertations form the backbone of a decade of mathematical ventures in the world of epistasis. The authors wish to acknowledge support from the Flemish Fund of Scienti?c - search (FWO-Vlaanderen) and of the Xunta de Galicia. They also wish to explicitly mentiontheintellectualandmoralsupporttheyreceivedthroughoutthepreparation of this work from their family and their colleagues Emilio Villanueva, Jose Mar'a Barja and Arnold Beckelheimer, as well as our local T T Xpert Jan Adriaenssens.
Initial training in pure and applied sciences tends to present problem-solving as the process of elaborating explicit closed-form solutions from basic principles, and then using these solutions in numerical applications. This approach is only applicable to very limited classes of problems that are simple enough for such closed-form solutions to exist. Unfortunately, most real-life problems are too complex to be amenable to this type of treatment. Numerical Methods - a Consumer Guide presents methods for dealing with them.
Shifting the paradigm from formal calculus to numerical computation, the text makes it possible for the reader to
Â· discover how to escape the dictatorship of those particular cases that are simple enough to receive a closed-form solution, and thus gain the ability to solve complex, real-life problems;
Â· understand the principles behind recognized algorithms used in state-of-the-art numerical software;
Â· learn the advantages and limitations of these algorithms, to facilitate the choice of which pre-existing bricks to assemble for solving a given problem; and
Â· acquire methods that allow a critical assessment of numerical results.
Numerical Methods - a Consumer Guide will be of interest to engineers and researchers who solve problems numerically with computers or supervise people doing so, and to students of both engineering and applied mathematics.
The Process of Social Research successfully meets two major challenges of teaching social science methods: to make the material interesting and accessible to students, and to provide them with the tools necessary to understand, evaluate, and conduct research. Authors Jeffrey C. Dixon, Royce A. Singleton, Jr., and Bruce C. Straits employ a conversational writing style that is engaging and student-friendly. Using everyday examples to introduce chapters and clarify complex concepts, they provide current research examples on such cutting-edge topics as immigration, family composition, prosecutorial misconduct, organized racism, homelessness, social inequality and education, and alcohol consumption and grades. Placing a unique emphasis on the research process, the book helps students understand the logic and mechanics of social research, giving them the tools and the power to evaluate the research of others and to conduct their own research. Beginning with the introduction, every chapter contains flowcharts of research processes. As each diagram is presented, the authors relate the specific method to the overall research process. Then, over the course of the chapter or section, they flesh out each step. This way, they convey information about the "nuts and bolts" of research while ensuring that students do not lose sight of the logic of inquiry.
Set-valued optimization is a vibrant and expanding branch of mathematics that deals with optimization problems where the objective map and/or the constraints maps are set-valued maps acting between certain spaces. Since set-valued maps subsumes single valued maps, set-valued optimization provides an important extension and unification of the scalar as well as the vector optimization problems. Therefore this relatively new discipline has justifiably attracted a great deal of attention in recent years. This book presents, in a unified framework, basic properties on ordering relations, solution concepts for set-valued optimization problems, a detailed description of convex set-valued maps, most recent developments in separation theorems, scalarization techniques, variational principles, tangent cones of forst and higher order, sub-differential of set-valued maps, generalized derivatives of set-valued maps, sensitivity analysis, optimality conditions, duality, and applications in economics among other things.
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