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5. Introduction

Author

Balázs Bánhelyi, Tibor Csendes, Balázs Lévai, László Pál, and Dániel Zombori

Published
2018

6. Local Search

Author

Balázs Bánhelyi, Tibor Csendes, Balázs Lévai, László Pál, and Dániel Zombori

Published
2018

7. The GLOBALJ Framework

Author

László Pál, Tibor Csendes, Dániel Zombori, Balázs Bánhelyi, and Balázs L. Lévai

Subjects
Software, Java, business.industry, Computer science, Workaround, Optimization methods, Software engineering, business, MATLAB, Implementation, Global optimization, computer, computer.programming_language
Abstract

The GLOBAL optimization method was designed in an era when researchers had to take into account the hardware limitations that meant much more difficulty back then, if they worked on practical optimization methods. The algorithm GLOBAL and all its implementations including the latest one in MATLAB have been carrying over workarounds of these past problems that are obsolete nowadays. The algorithm has no implementation on any of the modern programming platforms, while the available ones are not easy to use, customize, or integrate into larger software environments. This chapter introduces the GLOBALJ framework, a new, modularized JAVA implementation of an improved GLOBAL algorithm.

Published
2018

8. The GLOBAL Optimization Algorithm

Author

Dániel Zombori, Tibor Csendes, László Pál, Balázs Bánhelyi, and Balázs L. Lévai

Subjects
Java, Computer science, Global optimization algorithm, Parallel computing, computer, computer.programming_language
Published
2018

9. Parallelization

Author

Balázs Bánhelyi, Tibor Csendes, Balázs Lévai, László Pál, and Dániel Zombori

Published
2018

10. The GLOBAL Optimization Algorithm : Newly Updated with Java Implementation and Parallelization

Author

Balázs Bánhelyi, Tibor Csendes, Balázs Lévai, László Pál, Dániel Zombori, Balázs Bánhelyi, Tibor Csendes, Balázs Lévai, László Pál, and Dániel Zombori

Subjects
Mathematical optimization, Calculus of variations, Computer science—Mathematics, Operations research, Management science, Mathematical analysis
Abstract

This book explores the updated version of the GLOBAL algorithm which contains improvements for a local search algorithm and new Java implementations. Efficiency comparisons to earlier versions and on the increased speed achieved by the parallelization, are detailed. Examples are provided for students as well as researchers and practitioners in optimization, operations research, and mathematics to compose their own scripts with ease. A GLOBAL manual is presented in the appendix to assist new users with modules and test functions. GLOBAL is a successful stochastic multistart global optimization algorithm that has passed several computational tests, and is efficient and reliable for small to medium dimensional global optimization problems. The algorithm uses clustering to ensure efficiency and is modular in regard to the two local search methods it starts with, but it can also easily apply other local techniques. The strength of this algorithm lies in its reliability and adaptive algorithm parameters. The GLOBAL algorithm is free to download also in the earlier Fortran, C, and MATLAB implementations.

Published
2018

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