More than half of new businesses fail within five years, and many of those that endure can't seem to bridge the gulf between "just surviving" and true success. This book is a practical "how-to" guide for overcoming the hurdles that all entrepreneurs face when starting and growing a business. Serial entrepreneurs Matthew Michalewicz and Zbigniew Michalewicz provide countless "out-of-the-box" solutions for: winning that first major client; signing up partners and resellers; building an all-star management team; leveraging new customers from existing customers; impressing the media and analysts;...
More than half of new businesses fail within five years, and many of those that endure can't seem to bridge the gulf between "just surviving" and true...
This book is the only source that provides comprehensive, current, and correct information on problem solving using modern heuristics. It covers classic methods of optimization, including dynamic programming, the simplex method, and gradient techniques, as well as recent innovations such as simulated annealing, tabu search, and evolutionary computation. Integrated into the discourse is a series of problems and puzzles to challenge the reader. The book is written in a lively, engaging style and is intended for students and practitioners alike. Anyone who reads and understands the material...
This book is the only source that provides comprehensive, current, and correct information on problem solving using modern heuristics. It covers cl...
Genetic algorithms are founded upon the principle of evolution, i.e., survival of the fittest. Hence evolution programming techniques, based on genetic algorithms, are applicable to many hard optimization problems, such as optimization of functions with linear and nonlinear constraints, the traveling salesman problem, and problems of scheduling, partitioning, and control. The importance of these techniques is still growing, since evolution programs are parallel in nature, and parallelism is one of the most promising directions in computer science. The book is self-contained and the only...
Genetic algorithms are founded upon the principle of evolution, i.e., survival of the fittest. Hence evolution programming techniques, based on geneti...
Dipankar DasGupta Zbigniew Michalewicz D. DasGupta
Evolutionary algorithms are general-purpose search procedures based on the mechanisms of natural selection and population genetics. They are appealing because they are simple, easy to interface, and easy to extend. This volume is concerned with applications of evolutionary algorithms and associated strategies in engineering. It will be useful for engineers, designers, developers, and researchers in any scientific discipline interested in the applications of evolutionary algorithms. The volume consists of five parts, each with four or five chapters. The topics are chosen to emphasize...
Evolutionary algorithms are general-purpose search procedures based on the mechanisms of natural selection and population genetics. They are appealing...
Many advances have recently been made in metaheuristic methods, from theory to applications. The editors, both leading experts in this field, have assembled a team of researchers to contribute 21 chapters organized into parts on simulated annealing, tabu search, ant colony algorithms, general purpose studies of evolutionary algorithms, applications of evolutionary algorithms, and metaheuristics.
Many advances have recently been made in metaheuristic methods, from theory to applications. The editors, both leading experts in this field, have ...
The purpose of the Fifth International Conference on Statistical and Scientific Databases was to bring together database researchers, users, and system builders, to discuss the particular issues of interest and to propose new solutions to the problems of the area, both from the theoretical and from the application point of view. This proceedings volume contains three invited papers as well as the other 13 contributions.
The purpose of the Fifth International Conference on Statistical and Scientific Databases was to bring together database researchers, users, and syste...
Evolutionary Computation 2: Advanced Algorithms and Operators expands upon the basic ideas underlying evolutionary algorithms. The focus is on fitness evaluation, constraint-handling techniques, population structures, advanced techniques in evolutionary computation, and the implementation of evolutionary algorithms. It is intended to be used by individual researchers and students in the expanding field of evolutionary computation.
Evolutionary Computation 2: Advanced Algorithms and Operators expands upon the basic ideas underlying evolutionary algorithms. The focus is on fitness...
Fernando G. Lobo Claudio F. Lima Zbigniew Michalewicz
Covers a broad area of evolutionary computation, including genetic algorithms, genetic programming, and estimation of distribution algorithms. This book discusses the issues of specific parameters used in parallel implementations, multi-objective evolutionary algorithms, and practical consideration for real-world applications.
Covers a broad area of evolutionary computation, including genetic algorithms, genetic programming, and estimation of distribution algorithms. This bo...
This book is the only source that provides comprehensive, current, and correct information on problem solving using modern heuristics. It covers classic methods of optimization, including dynamic programming, the simplex method, and gradient techniques, as well as recent innovations such as simulated annealing, tabu search, and evolutionary computation. Integrated into the discourse is a series of problems and puzzles to challenge the reader. The book is written in a lively, engaging style and is intended for students and practitioners alike. Anyone who reads and understands the material...
This book is the only source that provides comprehensive, current, and correct information on problem solving using modern heuristics. It covers cl...
Genetic algorithms are founded upon the principle of evolution, i.e., survival of the fittest. Hence evolution programming techniques, based on genetic algorithms, are applicable to many hard optimization problems, such as optimization of functions with linear and nonlinear constraints, the traveling salesman problem, and problems of scheduling, partitioning, and control. The importance of these techniques is still growing, since evolution programs are parallel in nature, and parallelism is one of the most promising directions in computer science. The book is self-contained and the only...
Genetic algorithms are founded upon the principle of evolution, i.e., survival of the fittest. Hence evolution programming techniques, based on geneti...
