Explains metaheuristics at a basic level for easy understanding

Allows master's students with various backgrounds to understand and apply these techniques to decision-making problems in business analytics

No previous knowledge of programming languages such as Java or C++ is required

Introduces the concepts in a familiar environment (Microsoft Excel)

Autorentext

Abraham Duarte is an Associate Professor in the Computer Science Department at the Rey Juan Carlos University(Madrid, Spain). He received his doctoral degree in Computer Sciences from the Rey Juan Carlos University. His research is devoted to the development of models and solution methods based on meta-heuristics for combinatorial optimization problems. He has published more than 50 papers in SCI-JCR prestigious scientific journals such us European Journal of Operational Research, INFORMS Journal on Computing, Computational Optimization and Applications, or Computers & Operations Research. Dr. Duarte has also published 11 papers in non-indexed journals, 20 book chapters and more than 70 papers in conference proceedings. He has been the principal investigator on 5 competitive research projects with a total budget of 200000 euros (aprox.), he has been the advisor of 5 doctoral theses, and he is co-inventor of a US patent (US 20100138373 A1). Dr Duarte is reviewer of the Journal of Heuristic, Journal of Mathematical Modeling and Algorithms, INFORMS Journal on Computing, Applied Soft Computing, European Journal of Operational Research and Soft Computing. He is also member of the program committee of the conferences MAEB, HIS, ISDA, SOCO or MHIPL. Manuel Laguna is the MediaOne Professor of Management Science and Director of Global Initiatives at the Leeds School of Business of the University of Colorado Boulder. He started his academic career at the University of Colorado in 1990, after receiving master's (1987) and doctoral (1990) degrees in Operations Research and Industrial Engineering from the University of Texas at Austin.He has done extensive research in the interface between computer science, artificial intelligence and operations research, resulting in over one hundred publications, including four books. He has received research funding from private industry and government agencies such as the National Science Foundation, the Office of Naval Research and the Environmental Protection Agency. He is co-founder of OptTek Systems, a Boulder-based software and consulting company that provides optimization solutions. He is the editor-in-chief of the Journal of Heuristics and has been Division Chair, Senior Associate Dean and Interim Dean at the Leeds School of Business. Rafael Martí is Professor of Statistics and Operations Research at the University of Valencia, Spain. He received a doctoral degree in Mathematics from the University of Valencia in 1994. He has done extensive research in metaheuristics for hard optimization problems.Dr Martí has about 200 publications, half of them in indexed journals (JCR), including EJOR, Informs JoC, IIE Transactions, JOGO, C&OR, and Discrete and Applied Maths. He is the co-author of Scatter Search (Kluwer 2003) and The Linear Ordering Problem (Springer 2011) monographs, and has secured an American patent. Prof. Martí is currently Area Editor in the Journal of Heuristics,Associate Editor in the Math. Prog. Computation, and the Int. Journal of Metaheuristics. He is Senior Research Associate of OptTek Systems (USA), and has given about 50 invited and plenary talks. Dr. Martí has been invited Professor at the University of Colorado (USA), University of Molde (Norway), University of Graz (Austria), and University of Bretagne-Sud (France.)

Klappentext

Explains metaheuristics at a basic level for easy understanding Allows master's students with various backgrounds to understand and apply these techniques to decision-making problems in business analytics No previous knowledge of programming languages such as Java or C++ is required Introduces the concepts in a familiar environment (Microsoft Excel)

Zusammenfassung

Explains metaheuristics at a basic level for easy understanding

Allows master's students with various backgrounds to understand and apply these techniques to decision-making problems in business analytics

No previous knowledge of programming languages such as Java or C++ is required

Introduces the concepts in a familiar environment (Microsoft Excel)

Inhalt
Introduction to Spreadsheet Modelling and Metaheuristics.- General Concepts in Metaheuristic Search.- Greedy Randomized Adaptive Search Procedures.- Tabu Search.- Black-box Solvers.