Search results for "data structures and algorithms in java"
Items we need to order for you
Hybrid Algorithms for Service, Computing and Manufacturing Systems
Hybrid Algorithms for Service, Computing and Manufacturing Systems: Routing and Scheduling Solutions explores research developments and applications from an interdisciplinary perspective that combines approaches from operations research, computer science, artificial intelligence, and applied computational mathematics. Contributions cover a range of hybrid algorithm theory and practice as it relates to routing, scheduling, and real-life applications.
R 6,993.89
R 794.00
Evolutionary Algorithms
Evolutionary algorithms are bio-inspired algorithms based on Darwin’s theory of evolution. They are expected to provide non-optimal but good quality solutions to problems whose resolution is impracticable by exact methods. In six chapters, this book presents the essential knowledge required to efficiently implement evolutionary algorithms. Chapter 1 describes a generic evolutionary algorithm as well as the basic operators that compose it. Chapter 2 is devoted to the solving of continuous optimization problems, without constraint. Three leading approaches are described and compared on a set of test functions. Chapter 3 considers continuous optimization problems with constraints. Various approaches suitable for evolutionary methods are presented. Chapter 4 is related to combinatorial optimization. It provides a catalog of variation operators to deal with order-based problems. Chapter 5 introduces the basic notions required to understand the issue of multi-objective optimization and a variety of approaches for its application. Finally, Chapter 6 describes different approaches of genetic programming able to evolve computer programs in the context of machine learning.
R 5,795.00
R 611.00
R 945.95
R 1,143.68
R 763.00
Recent Algorithms and Applications in Swarm Intelligence Research
Advancements in the nature-inspired swarm intelligence algorithms continue to be useful in solving complicated problems in nonlinear, non-differentiable, and un-continuous functions as well as being applied to solve real-world applications. Recent Algorithms and Applications in Swarm Intelligence Research highlights the current research on swarm intelligence algorithms and its applications. Including research, survey and application papers, this book serves as a platform for students and scholars interested in achieving their studies on swarm intelligence algorithms and their applications.
R 7,562.69
R 1,152.64
R 1,025.55
R 2,227.52
R 519.00
Analysis of Algorithms
This text teaches the techniques needed to analyze algorithms. Organized by analysis techniques, The Analysis of Algorithms includes a systematic and largely self-contained treatment of the mathematics needed for elementary and intermediate analyses, as well as brief guides to the sources for more advanced techniques. Each technique is illustrated by being applied to the analysis of a realistic algorith. The authors provide explicit guidance on the use of various methods-for example, the discussion of mathematical induction emphasizes the process of finding the induction hypothesis, and the chapter on formulas for simplifying summations includes a section on deciding which formulas to apply. Many of the exercises give the student an opportunity to apply the techniques in developing original algorithm analyses.
R 6,267.00
Algorithms on Strings
The book is intended for lectures on string processes and pattern matching in Master's courses of computer science and software engineering curricula. The details of algorithms are given with correctness proofs and complexity analysis, which make them ready to implement. Algorithms are described in a C-like language. The book is also a reference for students in computational linguistics or computational biology. It presents examples of questions related to the automatic processing of natural language, to the analysis of molecular sequences, and to the management of textual databases.
R 6,577.42
R 704.00
Algorithmentheorie
Die Algorithmentheorie ist Ende der dreiBiger Jahre entstanden in Ver- bindung mit Problemen der mathematischen Logik. Hit dem Aufkommen einer wissenschaftlich fundierten Informatik hat sie, insbesondere in den letzten zwanzig Jahren, an Bedeutung und Tragweite gewonnen. Das wird begreiflich, wenn man bedenkt, daB ein Programm flir eine elektronische Rechenanlage im wesentlichen ein Algorithmus ist und daB Resultate der Algorithmentheorie deshalb auch auf Programme anwendbar sind. Insbeson- dere gibt es eine enge Verbindung zwischen der Algorithmentheorie und anderen flir die Informatik bedeutsamen Zweigen, wie der Automatentheorie, der Theorie der formalen Sprachen und der sich in den letzten Jahren heranbildenden Theorie der Programmierung. Wahrend die meisten Blicher liber Algorithmentheorie sich an Studenten der mathematischen Logik richten, ist dieses Buch flir Informatikstuden- ten bestimmt. Zwar wird das Thema mit mathematischer Scharfe behandelt, aber es werden keine besonderen mathematischen Kenntnisse vorausgesetzt und die zahlreichen Kommentare zielen daraufhin, ein gutes intuitives Verstandnis zu ermoglichen; auBerdem hebt das Buch regelmaBig die Be- deutung der Resultate flir die Informatik hervor. SchlieBlich sind die Notationen und bestimmte Beweismethoden der Automatentheorie und der Theorie der formalen Sprachen entnommen; insbesondere wird grundsatz- lich mit Worten statt mit natlirlichen Zahlen gearbeitet.
R 2,442.03
R 608.00
R 6,258.00
Parameterized Algorithms
This comprehensive textbook presents a clean and coherent account of most fundamental tools and techniques in Parameterized Algorithms and is a self-contained guide to the area. The book covers many of the recent developments of the field, including application of important separators, branching based on linear programming, Cut & Count to obtain faster algorithms on tree decompositions, algorithms based on representative families of matroids, and use of the Strong Exponential Time Hypothesis. A number of older results are revisited and explained in a modern and didactic way.The book provides a toolbox of algorithmic techniques. Part I is an overview of basic techniques, each chapter discussing a certain algorithmic paradigm. The material covered in this part can be used for an introductory course on fixed-parameter tractability. Part II discusses more advanced and specialized algorithmic ideas, bringing the reader to the cutting edge of current research. Part III presents complexity results and lower bounds, giving negative evidence by way of W[1]-hardness, the Exponential Time Hypothesis, and kernelization lower bounds.All the results and concepts are introduced at a level accessible to graduate students and advanced undergraduate students. Every chapter is accompanied by exercises, many with hints, while the bibliographic notes point to original publications and related work.
R 2,198.00
Algorithmen
Zu den wichtigen und fundamentalen Konzepten der Informatik gehört sicher das des Algorithmus. Seit man sich mit Maschinen beschäftigt, die einfache mathematische Operationen ausführen können, befaßt man sich mit den Problemen, was überhaupt berechnet werden kann und wie diese Berechnungen effizient durchgeführt werden können. Durch die Erfindung des Computers wurde die Behandlung dieser Fragen stark ge fördert; dies hat zur Entdeckung vieler wichtiger und ideenreicher Algorithmen geführt. Das Studium von Algorithmen ist ein besonderes Anliegen der Informatik. In diesem Buch wollen wir die Kenntnisse über Algorithmen in zusammenhängender Weise so darstellen, daß sowohl Stu denten als auch in der Praxis Tätige den Entwurf und die Analyse neuer Algorithmen erlernen können. Ein Buch, das jeden Algorithmus enthält, der jemals erfunden wur de, müßte einen enormen Umfang haben. Daher beschränkt man sich übli cherweise bei Büchern über Algorithmen auf wenige Problembereiche, die dann im Detail behandelt werden. Zu jedem speziellen Problem wird der effizienteste Lösungsalgorithmus vorgestellt und analysiert. Da wir mehrere Jahre lang Kurse nach dieser Methode abgehalten haben, kennen wir den großen Nachteil dieses Verfahrens. Der Student lernt zwar viele schnelle Algorithmen kennen und kann diese auch analysie ren, im Entwurf guter Algorithmen bleibt er aber unsicher.
R 2,038.95
Algorithms For Analysis, Inference, And Control Of Boolean Networks
The Boolean network (BN) is a mathematical model of genetic networks and other biological networks. Although extensive studies have been done on BNs from a viewpoint of complex systems, not so many studies have been undertaken from a computational viewpoint. This book presents rigorous algorithmic results on important computational problems on BNs, which include inference of a BN, detection of singleton and periodic attractors in a BN, and control of a BN. This book also presents algorithmic results on fundamental computational problems on probabilistic Boolean networks and a Boolean model of metabolic networks. Although most contents of the book are based on the work by the author and collaborators, other important computational results and techniques are also reviewed or explained.
R 3,497.44
R 458.00
R 703.94
R 611.00
Stable Mutations for Evolutionary Algorithms
This book presents a set of theoretical and experimental results that describe the features of the wide family of α-stable distributions (the normal distribution also belongs to this class) and their various applications in the mutation operator of evolutionary algorithms based on real-number representation of the individuals, and, above all, equip these algorithms with features that enrich their effectiveness in solving multi-modal, multi-dimensional global optimization problems. The overall conclusion of the research presented is that the appropriate choice of probabilistic model of the mutation operator for an optimization problem is crucial.Mutation is one of the most important operations in stochastic global optimization algorithms in the n-dimensional real space. It determines the method of search space exploration and exploitation. Most applications of these algorithms employ the normal mutation as a mutation operator. This choice is justified by the central limit theorem but is associated with a set of important limitations. Application of α-stable distributions allows more flexible evolutionary models to be obtained than those with the normal distribution. The book presents theoretical analysis and simulation experiments, which were selected and constructed to expose the most important features of the examined mutation techniques based on α-stable distributions. It allows readers to develop a deeper understanding of evolutionary processes with stable mutations and encourages them to apply these techniques to real-world engineering problems.
R 4,030.00
R 489.00
Evolutionary Optimization Algorithms
This comprehensive reference text discusses evolutionary optimization techniques, to find optimal solutions for single and multi-objective problems.The text presents each evolutionary optimization algorithm along with its history and other working equations. It also discusses variants and hybrids of optimization techniques. The text presents step-by-step solution to a problem and includes software’s like MATLAB and Python for solving optimization problems. It covers important optimization algorithms including single objective optimization, multi objective optimization, Heuristic optimization techniques, shuffled frog leaping algorithm, bacteria foraging algorithm and firefly algorithm.Aimed at senior undergraduate and graduate students in the field of electrical engineering, electronics engineering, mechanical engineering, and computer science and engineering, this text: Provides step-by-step solution for each evolutionary optimization algorithm. Provides flowcharts and graphics for better understanding of optimization techniques. Discusses popular optimization techniques include particle swarm optimization and genetic algorithm. Presents every optimization technique along with the history and working equations. Includes latest software like Python and MATLAB.
R 2,757.23
