Global optimization advances in Mixed-Integer Nonlinear Programming, MINLP, and Constrained Derivative-Free Optimization, CDFO

•We review the recent advances in global optimization for Mixed Integer Nonlinear Programming, MINLP.•We review the recent advances in global optimization for Constrained Derivative-Free optimization, CDFO.•We present theoretical contributions, software implementations and applications for both MINL...

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Bibliographic Details
Published inEuropean journal of operational research Vol. 252; no. 3; pp. 701 - 727
Main Authors Boukouvala, Fani, Misener, Ruth, Floudas, Christodoulos A.
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier B.V 01.08.2016
Elsevier Sequoia S.A
Subjects
Algorithms
Applications programs
Benchmarking
Benchmarks
Computer programs
Constraints
Derivative-free
Deterministic global optimization
Grey-/Black-box
Integer programming
Literature reviews
Mathematical problems
MINLP
Nonlinear programming
Optimization
Optimization algorithms
Software packages
Studies
MINLP
Grey-/Black-box
Constraints
Deterministic global optimization
Derivative-free
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Summary:•We review the recent advances in global optimization for Mixed Integer Nonlinear Programming, MINLP.•We review the recent advances in global optimization for Constrained Derivative-Free optimization, CDFO.•We present theoretical contributions, software implementations and applications for both MINLP and CDFO.•We discuss possible interactions between the two areas of MINLP and CDFO.•We present a complete test suite for MINLP and CDFO algorithms. This manuscript reviews recent advances in deterministic global optimization for Mixed-Integer Nonlinear Programming (MINLP), as well as Constrained Derivative-Free Optimization (CDFO). This work provides a comprehensive and detailed literature review in terms of significant theoretical contributions, algorithmic developments, software implementations and applications for both MINLP and CDFO. Both research areas have experienced rapid growth, with a common aim to solve a wide range of real-world problems. We show their individual prerequisites, formulations and applicability, but also point out possible points of interaction in problems which contain hybrid characteristics. Finally, an inclusive and complete test suite is provided for both MINLP and CDFO algorithms, which is useful for future benchmarking.
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ISSN:0377-2217
1872-6860
DOI:10.1016/j.ejor.2015.12.018