Titlebook: Derivative-free DIRECT-type Global Optimization; Applications and Sof Linas Stripinis,Remigijus Paulavi?ius Book 2023 The Editor(s) (if app

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Derivative-free DIRECT-type Global Optimization978-3-031-46537-6Series ISSN 2190-8354 Series E-ISSN 2191-575X

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978-3-031-46539-0The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl

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Facility Location with Chance Constraintsive-free techniques for global optimization. Specifically, we will position the . algorithm within other derivative-free global solution techniques, while also exploring its popularity and the diverse range of applications. By doing so, the readers will gain valuable insights into the significance a

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Facility Location Under Uncertaintyciency. This chapter provides a comprehensive review of the advancements made in the development of novel approaches and extensions of the . algorithm. Although the original . algorithm and its modifications were primarily designed for solving box-constrained global optimization problems, this chapt

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Francisco Saldanha-da-Gama,Shuming Wangof these algorithms. Various software tools, including the . toolbox and the . algorithmic framework, are discussed in detail. Furthermore, this chapter provides an overview of the . library, which includes a collection of global optimization tests and practical problems in the real world. We conduc

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The Role of the , Algorithm in Derivative-Free Global Optimization,hile also exploring its popularity and the diverse range of applications. By doing so, the readers will gain valuable insights into the significance and role of . in the context of solving complex global optimization challenges.

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Book 2023m well-known experts on the subject. A primary focus of this book is the well-known class of deterministic DIRECT (DIviding RECTangle)-type algorithms. This book describes a new set of algorithms derived from newly developed partitioning, sampling, and selection approaches in the box- and generally-