Evolution and Optimization (Mathematical Ecology)
by Hans-Michael Voigt
A fun and stunningly illustrated introduction to the art of linear optimizationLinear optimization is a powerful modeling method for discovering the best solution to a problem among a set of available alternatives. It is one of today's most important branches of mathematics and computer science-and also a surprisingly rich medium for creating breathtaking works of art. Opt Art takes readers on an entertaining tour of linear optimization and its applications, showing along the way how it can be u...
This guide provides a roadmap for students transitioning from an undergraduate mathematics curriculum and degree into a graduate mathematics curriculum and program. It discusses a selection of concepts and ideas that are central in mathematics and found in a wide range of areas ranging from pure to applied mathematics developing the readers' self-reliance and independence as mathematical thinkers.
Optimierungsverfahren Und Pascal-Programme (Anwender-PROBLEME, Mathematische VERFAHREN, Computer-PROGRAMME, #2)
by Claus Richter and Bernd Renner
Modeling and Solution of Continuous Set Covering Problems by Means of semi-infinite Optimization.
by Helene Krieg
This work is designed to act as a supplementary text for those using or beginning to use Mathematica, the sophisticated mathematical software system. Topics covered include calculus, linear algebra, ordinary and partial differential equations, discrete mathematics and more.
Reservoir operation is a multi-objective optimization problem, and is traditionally solved with dynamic programming (DP) and stochastic dynamic programming (SDP) algorithms. The thesis presents novel algorithms for optimal reservoir operation, named nested DP (nDP), nested SDP (nSDP), nested reinforcement learning (nRL) and their multi-objective (MO) variants, correspondingly MOnDP, MOnSDP and MOnRL. The idea is to include a nested optimization algorithm into each state transition, which reduces...
The quality loss function, introduced by Japanese engineer, statistician and scientist Dr. Genichi Taguchi in the 1980s, is still one of the most interesting topics in applied industrial statistics and quality engineering and management, which presented a paradigm shift in quality loss and product, process and/or system quality conception. Taguchi emphasized a proactive approach toward quality in terms of embedding quality requirements into the design of product, process and/or system, which hig...
Advanced Statistical Modeling and Design of Experiments Using MATLAB
by P Braselton
60 Worksheets - Identifying Smallest Number of 6 Digits (60 Days Math Smallest Numbers, #5)
by Kapoo Stem
The Classical Moment Problem: and Some Related Questions in Analysis
by N I Akhiezer
Synchronization Of Systems With Time-delayed Coupling (World Scientific Series on Nonlinear Science. Series a, #0)
by Erik Steur, Toshiki Oguchi, and Henk Nijmeijer
The book aims to provide the tools for analyzing the synchronization of identical systems under time-delayed coupling. On the structural assumption that the system itself is semi-passive - i.e. the system is behaving as a passive system outside some ball-conditions ensuring synchronization of two systems under time-delayed coupling - the framework is extended to the more general situation of a network with time-delayed diffusive coupling. Conditions are derived for time-delay and coupling streng...
Mathematics in Early Childhood (Towards an Ethical Praxis in Early Childhood)
Structured around Bishop's six fundamental mathematical activities, this book brings together examples of mathematics education from a range of countries to help readers broaden their view on maths and its interrelationship to other aspects of life. Considering different educational traditions and diverse contexts, and illustrating theory through the use of real-life vignettes throughout, this book encourages readers to review, reflect on, and critique their own practice when conducting activit...
Offers an overview of the MM principle, a device for deriving optimization algorithms satisfying the ascent or descent property. These algorithms can:Separate the variables of a problem. Avoid large matrix inversions. Linearize a problem. Restore symmetry.Deal with equality and inequality constraints gracefully. Turn a non-differentiable problem into a smooth problem. The author: Presents the first extended treatment of MM algorithms, which are ideal for high-dimensional optimization problems in...
Stochastic Control and Mathematical Modeling (Encyclopedia of Mathematics and its Applications)
by Hiroaki Morimoto
This is a concise and elementary introduction to stochastic control and mathematical modelling. This book is designed for researchers in stochastic control theory studying its application in mathematical economics and those in economics who are interested in mathematical theory in control. It is also a good guide for graduate students studying applied mathematics, mathematical economics, and non-linear PDE theory. Contents include the basics of analysis and probability, the theory of stochastic...
Combinatorial Optimization (Algorithms and Combinatorics, #21)
by Bernhard Korte and Jens Vygen
This comprehensive textbook on combinatorial optimization puts special emphasis on theoretical results and algorithms with provably good performance, in contrast to heuristics. It has arisen as the basis of several courses on combinatorial optimization and more special topics at graduate level. Since the complete book contains enough material for at least four semesters (4 hours a week), one usually selects material in a suitable way. The book contains complete (but concise) proofs, also for man...
A game is an efficient model of interactions between agents, for the following basic reason: the players follow fixed rules, have interests on all possible final outcomes of the game, and the final result for them does not depend only from the choices they individually make, but also from the choices of other agents. Thus the focus is actually on the fact that in a game there are several agents interacting. In fact, more recently this theory took the name of Interactive Decision Theory. It is re...
Combinational optimization (CO) is a topic in applied mathematics, decision science and computer science that consists of finding the best solution from a non-exhaustive search. CO is related to disciplines such as computational complexity theory and algorithm theory, and has important applications in fields such as operations research/management science, artificial intelligence, machine learning, and software engineering.Advances in Combinatorial Optimization presents a generalized framework fo...
Nonlinear Optimization of Vehicle Safety Structures
by Jesper Christensen and Christophe Bastien
Nonlinear Optimization of Vehicle Safety Structures: Modeling of Structures Subjected to Large Deformations provides a cutting-edge overview of the latest optimization methods for vehicle structural design. The book focuses on large deformation structural optimization algorithms and applications, covering the basic principles of modern day topology optimization and comparing the benefits and flaws of different algorithms in use. The complications of non-linear optimization are highlighted, al...
The Simplex Method of Linear Programming (Dover Books on Mathematics)
by F.A. Ficken