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Scheduling Algorithms
Scheduling Algorithms
From the reviews of the fourth edition: 

"This is a book about scheduling algorithms. … The book contains eleven chapters. … Most of the chapters contain the summarized complexity results. In this edition the complexity columns have been updated. The book is completed by the bibliography which also has been updated and...

Clean Code: A Handbook of Agile Software Craftsmanship (Robert C. Martin Series)
Clean Code: A Handbook of Agile Software Craftsmanship (Robert C. Martin Series)

Even bad code can function. But if code isn’t clean, it can bring a development organization to its knees. Every year, countless hours and significant resources are lost because of poorly written code. But it doesn’t have to be that way.

Noted software expert Robert C. Martin presents a revolutionary paradigm with
...

Experimental Research in Evolutionary Computation: The New Experimentalism (Natural Computing Series)
Experimental Research in Evolutionary Computation: The New Experimentalism (Natural Computing Series)

Experimentation is necessary - a purely theoretical approach is not reasonable. The new experimentalism, a development in the modern philosophy of science, considers that an experiment can have a life of its own. It provides a statistical methodology to learn from experiments, where the experimenter should distinguish between statistical...

Information Processing with Evolutionary Algorithms: From Industrial Applications to Academic Speculations
Information Processing with Evolutionary Algorithms: From Industrial Applications to Academic Speculations
The last decade of the twentieth century has witnessed a surge of interest in numerical, computational intensive approaches to information processing. The lines that draw the boundaries between statistics, optimization, artificial intelligence and information processing are disappearing and it is not uncommon to find well founded and sophisticated...
Object-Oriented Design Heuristics
Object-Oriented Design Heuristics
Upon completion of an object-oriented design, you are faced with a troubling question: "Is it good, bad, or somewhere in between?" Seasoned experts often answer this question by subjecting the design to a subconscious list of guidelines based on their years of experience. Experienced developer Arthur J. Riel has captured this elusive,...
Software Engineering Foundations: A Software Science Perspective
Software Engineering Foundations: A Software Science Perspective
A groundbreaking book in this field, Software Engineering Foundations: A Software Science Perspective integrates the latest research, methodologies, and their applications into a unified theoretical framework. Based on the author's 30 years of experience, it examines a wide range of underlying theories from philosophy, cognitive informatics,...
Automatic Design of Decision-Tree Induction Algorithms (SpringerBriefs in Computer Science)
Automatic Design of Decision-Tree Induction Algorithms (SpringerBriefs in Computer Science)

Presents a detailed study of the major design components that constitute a top-down decision-tree induction algorithm, including aspects such as split criteria, stopping criteria, pruning and the approaches for dealing with missing values. Whereas the strategy still employed nowadays is to use a 'generic' decision-tree induction...

Foundations of Learning Classifier Systems (Studies in Fuzziness and Soft Computing)
Foundations of Learning Classifier Systems (Studies in Fuzziness and Soft Computing)
Learning Classifier Systems (LCS) [Holland, 1976] are a machine learning technique which combines evolutionary computing, reinforcement learning, supervised learning or unsupervised learning, and heuristics to produce adaptive systems. They are rulebased systems, where the rules are usually in the traditional production system form of “IF...
Spatially Structured Evolutionary Algorithms: Artificial Evolution in Space and Time (Natural Computing Series)
Spatially Structured Evolutionary Algorithms: Artificial Evolution in Space and Time (Natural Computing Series)
Evolutionary algorithms (EAs) is now a mature problem-solving family of heuristics that has found its way into many important real-life problems and into leading-edge scientific research. Spatially structured EAs have different properties than standard, mixing EAs. By virtue of the structured disposition of the population members they bring about...
Evolutionary Computation in Combinatorial Optimization: 6th European Conference, EvoCOP 2006
Evolutionary Computation in Combinatorial Optimization: 6th European Conference, EvoCOP 2006
Metaheuristics have often been shown to be effective for difficult combinatorial optimization problems appearing in various industrial, economical, and scientific domains. Prominent examples of metaheuristics are evolutionary algorithms, simulated annealing, tabu search, scatter search, memetic algorithms, variable neighborhood search, iterated...
Metaheuristics: Progress in Complex Systems Optimization (Operations Research/Computer Science Interfaces Series)
Metaheuristics: Progress in Complex Systems Optimization (Operations Research/Computer Science Interfaces Series)
Metaheuristics has grown and continues to grow steadily. Seen both from the technical point of view and from the application-oriented side, these optimization tools have established their value in a remarkable story of success. Researchers have demonstrated the ability of these methods to solve hard combinatorial problems of practical sizes within...
Adaptive and Multilevel Metaheuristics (Studies in Computational Intelligence)
Adaptive and Multilevel Metaheuristics (Studies in Computational Intelligence)
One of the keystones in practical metaheuristic problem-solving is the fact that tuning the optimization technique to the problem under consideration is crucial for achieving top performance. This tuning/customization is usually in the hands of the algorithm designer, and despite some methodological attempts, it largely remains a scientific art....
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