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Computer Science | Zbigniew Michalewicz

Zbigniew Michalewicz

Academic Profile 

Dr. Zbigniew Michalewicz
Internationally renowned new technologies expert, Zbigniew Michalewicz has published over 200 articles and 15 books on the subject of predictive data mining and logistics optimisation.
He is Professor Emeritus at the University of Adelaide.
He received his Ph.D. from the Institute of Computer Science, Polish Academy of Sciences, in 1981. He also holds a Doctor of Science degree in Computer Science from the Polish Academy of Science, and in 2002 he received the title of “Professor” from the President of Poland, Mr. Alexander Kwasniewski.
He holds Professor positions at the Institute of Computer Science, Polish Academy of Sciences, the Polish–Japanese Institute of Information Technology, and the State Key Laboratory of Software Engineering of Wuhan University, China. He is also associated with the Structural Complexity Laboratory at Seoul National University, South Korea.
Zbigniew Michalewicz has also served as the Chairman of the Technical Committee on Evolutionary Computation, and later as the Executive Vice President of the IEEE Neural Network Council.

Business Profile 

Prof. Michalewicz was a co-founder, Chairman and Chief Scientific Officer of SolveIT Software Pty. Ltd., a company specialising in custom software solutions for demand forecasting, scheduling, supply chain optimisation and mine optimisation solutions. Customers include Rio Tinto Iron Ore, Rio Tinto Simandou, Xstrata Coal, Xstrata Copper, Xstrata Zinc, BHP Billiton Iron Ore, BMA Coal, Fortescue Metals Group, Hancock Prospecting and Pacific National Coal.
He has over 30 years of industry experience, and possesses expert knowledge of many artificial intelligence methods and modern heuristics. He has led numerous data mining and optimisation projects for major corporations and for several government agencies in the United States of America and Poland, and his scientific and business achievements have been recognized by publications such as TIME Magazine, Newsweek, The New York Times, Forbes, and the Associated Press.
Prof. Michalewicz recently co-founded a new company, Complexica, which will develop next-generation applications for cognitive computing.

ABI – Adaptive Business Intelligence 

Book: Adaptive Business Intelligence
Authors: Zbigniew Michalewicz, Martin Schmidt, Matthew Michalewicz, Constantin Chiriac
ISBN: 978-3-540-32928-2
In the modern information era, managers must recognize the competitive opportunities represented by decision-support tools. Adaptive business intelligence systems combine prediction and optimization techniques to assist decision makers in complex, rapidly changing environments. These systems address the fundamental questions: What is likely to happen in the future? And what is the best decision right now? Adaptive Business Intelligence includes elements of data mining, predictive modeling, forecasting, optimization, and adaptability.
The authors have considerable academic research backgrounds in artificial intelligence and related fields, combined with years of practical consulting experience in businesses and industries worldwide. In this book they explain the science and application of numerous prediction and optimization techniques, as well as how these concepts can be used to develop adaptive systems. The techniques covered include linear regression, time-series forecasting, decision trees and tables, artificial neural networks, genetic programming, fuzzy systems, genetic algorithms, simulated annealing, tabu search, ant systems, and agent-based modeling.
This book is suitable for business and IT managers who make decisions in complex industrial and service environments, nonspecialists who want to understand the science behind better predictions and decisions, and students and researchers who need a quick introduction to this field.

Metaheuristics for Hard Optimization 

Book: Advances in Metaheuristics for Hard Optimization
Editors: Patrick Siarry, Zbigniew Michalewicz
ISBN: 978-3-540-72959-4
Many advances have been made recently 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 various metaheuristics.
The book gathers contributions related to the following topics: theoretical developments in metaheuristics; adaptation of discrete metaheuristics to continuous optimization; performance comparisons of metaheuristics; cooperative methods combining different approaches; parallel and distributed metaheuristics for multiobjective optimization; software implementations; and real-world applications.
This book is suitable for practitioners, researchers and graduate students in disciplines such as optimization, heuristics, operations research, and natural computing.

How to Solve It: Modern Heuristics 

Book: How to Solve It: Modern Heuristics, 2nd ed.
Authors: Zbigniew Michalewicz, David B. Fogel
ISBN: 978-3-540-22494-5
"Michalewicz and Fogel make no effort to conceal their admiration for Polya’s classic work, now nearly six decades old, How to Solve It: a New Aspect of Mathematical Method. They borrow from this masterpiece not only their title, but also their predilection for using numerous puzzles as a way to engage readers’ minds and highlight discussion topics. ... Like its predecessor, the new How to solve it combines deep mathematical insight with skilled pedagogy. Puzzle lovers will seek out the book for its insightful discussion of many intriguing brain twisters. Students of computational methods will find it an accessible but rigorous introduction to evolutionary algorithms. Teachers will learn from its exposition how to make their own subject matter clearer to their students. Polya would be honored to know that his spirit lives on in the computer age." [ACM Computing Reviews, 01/02/01, H. Van Dyke Paranuk]

Genetic Algorithms 

Book: Genetic Algorithms + Data Structures = Evolution Programs, 3rd ed.
Author: Zbigniew Michalewicz
ISBN: 978-3-540-60676-5
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 prerequisite is basic undergraduate mathematics. This third edition has been substantially revised and extended by three new chapters and by additional appendices containing working material to cover recent developments and a change in the perception of evolutionary computation.

Parameter Setting in Evolutionary Algorithms 

Book: Parameter Setting in Evolutionary Algorithms
Editors: Fernando G. Lobo, Cláudio F. Lima, Zbigniew Michalewicz
ISBN: 978-3-540-69431-1
One of the main difficulties when applying an evolutionary algorithm -- or any heuristic method -- to a given problem is to decide on an appropriate set of parameter values. Typically these are specified before the algorithm is run and include population size, selection rate, operator probabilities, not to mention the representation and the operators themselves. This book gives the reader a solid perspective on the different approaches that have been proposed to automate control of these parameters as well as understanding their interactions. The book covers a broad area of evolutionary computation, including genetic algorithms, evolution strategies, genetic programming, and estimation of distribution algorithms, and also discusses the issues of specific parameters used in parallel implementations, multiobjective evolutionary algorithms, and practical consideration for real-world applications. It is a recommended read for researchers and practitioners of evolutionary computation and heuristic methods.

Evolutionary Algorithms 

Evolutionary Algorithms in Engineering Applications
Book: Evolutionary Algorithms in Engineering Applications
Authors: Dipankar Dasgupta, Zbigniew Michalewicz
ISBN: 978-3-540-62021-1
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. The book topics are chosen to emphasize application areas in different fields of engineering. Each chapter can be used for self-study or as a reference for practitioners.

Design by Evolution 

Book: Design by Evolution -- Advances in Evolutionary Design
Editors: Philip F. Hingston, Luigi C. Barone, Zbigniew Michalewicz
ISBN: 978-3-540-74109-1
Evolution is Nature’s design process. The natural world is full of wonderful examples of its successes, from engineering design feats such as powered flight, to the design of complex optical systems such as the mammalian eye, to the merely stunningly beautiful designs of orchids or birds of paradise. With increasing computational power, we are now able to simulate this process with greater fidelity, combining complex simulations with high-performance evolutionary algorithms to tackle problems that used to be impractical.
This book showcases the state of the art in evolutionary algorithms for design. The chapters are organized by experts in the following fields: evolutionary design and "intelligent design" in biology, art, computational embryogeny, and engineering. The book will be of interest to researchers, practitioners and graduate students in natural computing, engineering design, biology and the creative arts.

Variants of Evolutionary Algorithms for Real-World Algorithms 

Book: Variants of Evolutionary Algorithms for Real-World Algorithms
Editors: Raymond Chiong, Thomas Weise, Zbigniew Michalewicz
ISBN 978-3-642-23423-1
Evolutionary algorithms (EAs) are population-based, stochastic search algorithms that mimic natural evolution. Due to their ability to find excellent solutions for conventionally hard and dynamic problems within acceptable time, EAs have attracted interest from many researchers and practitioners in recent years.
This book “Variants of Evolutionary Algorithms for Real-World Applications” aims to promote the practitioner’s view on EAs by providing a comprehensive discussion of how EAs can be adapted to the requirements of various applications in the real-world domains. It comprises 14 chapters, including an introductory chapter revisiting the fundamental question of what an EA is and other chapters addressing a range of real-world problems such as production process planning, inventory system and supply chain network optimisation, task-based jobs assignment, planning for CNC-based work piece construction, mechanical/ship design tasks that involve runtime-intense simulations, data mining for the prediction of soil properties, automated tissue classification for MRI images, and database query optimisation, among others.
These chapters demonstrate how different types of problems can be successfully solved using variants of EAs and how the solution approaches are constructed, in a way that can be understood and reproduced with little prior knowledge on optimisation.

Guide to Teaching Puzzle-Based Learning 

Book: Guide to Teaching Puzzle-Based Learning
Authors: Edwin F. Meyer III, Nickolas Falkner, Raja Sooriamurthi, Zbigniew Michalewicz
This is a foundational approach to develop the critical thinking skills and mental stamina essential for solving real-world problems. It provides invaluable insights drawn from the authors’ extensive teaching experience. Practical advice is provided for teachers and lecturers evaluating a range of different formats for varying class sizes, based on results from classes taught in many different countries.
Topics and features: suggests numerous entertaining puzzles designed to motivate students to think about framing and solving unstructured problems; discusses models for student engagement, setting up puzzle clubs, hosting a puzzle competition, and various warm-up activities; presents an overview of effective teaching approaches, covering a variety of class activities, assignment settings and assessment strategies; examines the issues involved in framing a problem, and reviews a range of problem-solving strategies; contains tips for teachers and notes on common student pitfalls throughout the text; and provides a collection of puzzle sets for use during a puzzle-based learning event, including puzzles that require probabilistic reasoning, and logic and geometry puzzles.
This unique textbook/guide will be of great interest to instructors on all levels who wish to experiment with this approach, which has been successfully applied in universities, high schools, professional organizations and leading companies.


Evolutionary Algorithms, Evolutionary Computing, Genetic Algorithms, Heuristics, Adaptive Business Intelligence, ABI, Zbyszek Michalewicz