"Optimization for Black-Box Objective Functions"

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Book	Author(s)	Year	Publisher
Non-Convex Multi-Objective Optimization	Panos M. Pardalos; Antanas Žilinskas; Julius Žilinskas	1st ed. 2017	Springer International Publishing
Mathematics of Multi Objective Optimization	P. Serafini	1985	Springer Vienna
Archiving Strategies for Evolutionary Multi-objective Optimization Algorithms	Oliver Schütze; Carlos Hernández	1st ed. 2021	Springer International Publishing
Probability-Based Multi-objective Optimization for Material Selection	Maosheng Zheng; Haipeng Teng; Jie Yu; Ying Cui; Yi Wang	1st ed. 2023	Springer Nature Singapore
Black Box Optimization, Machine Learning, and No-Free Lunch Theorems	Panos M. Pardalos; Varvara Rasskazova; Michael N. Vrahatis	1st ed. 2021	Springer International Publishing
Black Box	Alexander Dallin	1985	University of California Press
Black box /	Repac, Nicolas,
Black box /	Doran, Christy,; Balasubramoniam, Muthuswamy,
Black box /	Belieu, Erin,	c2006.	Copper Canyon Press,
Black Box	Julie Schumacher	2008	Random House Children's Books
Black Box	Cassia Leo	2014	Transworld Publishers Limited
BLACK BOX	CLIFF JACKMAN	2015	MANOR House Publishing IN
Dynamic Programming Multi-Objective Combinatorial Optimization	Michal Mankowski; Mikhail Moshkov	1st ed. 2021	Springer International Publishing
Multi-Objective Optimization Using Evolutionary Algorithms	Kalyanmoy Deb	2001	Wiley
Pseudolinear Functions and Optimization	Shashi Kant Mishra; Balendu Bhooshan Upadhyay	2014	Routledge
Submodular Functions and Optimization	Satoru Fujishige	1991	Elsevier
Submodular Functions and Optimization	Satoru Fujishige	2005	Elsevier
Characterizing properties of stochastic objective functions	Susan Athey	1995	Dept. of Economics, Massachusetts Institute of Technology
Characterizing properties of stochastic objective functions	Susan Athey	1998	Massachusetts Institute of Technology
The black box	Thelma Lientz	1929	Saalfield
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Chapter	Author(s)	Book	Book Authors	Year	Publisher
Optimization for Black-Box Objective Functions	H. Nakayama, M. Arakawa and K. Washino	Optimization and optimal control /	Pardalos, P. M.; Tseveendorj, Ider.; Ėnkhbat, R.	[2003], ©2003.	World Scientific,
On Sampling Methods for Costly Multi-Objective Black-Box Optimization	Ingrida Steponavičė; Mojdeh Shirazi-Manesh; Rob J. Hyndman; Kate Smith-Miles; Laura Villanova	Advances in Stochastic and Deterministic Global Optimization	Panos M. Pardalos; Anatoly Zhigljavsky; Julius Žilinskas	1st ed. 2016	Springer International Publishing
Bayesian Optimization Objective Functions		Matlab. Statistics and Machine Learning Toolbox. User's Guide		2021	MathWorks
Bayesian Optimization Objective Functions		MATLAB Statistics and Machine Learning Toolbox™ User's Guide	The MathWorks, Inc.	2020	The MathWorks, Inc.
9123 Objective Functions for Treatment Optimization		Comprehensive Biomedical Physics. Volume 1. Nuclear Medicine And Molecular Imaging; Volume 2. X-ray And Ultrasound Imaging; Volume 3. Magnetic Resonance Imaging And Spectroscopy; Volume 4. Optical Molecular Imaging; Volume 5. Physics Of Physiological Measurements; Volume 6. Bioinformatics; Volume 7. Radiation Biology And Radiation Safety; Volume 8. Radiation Sources And Detectors; Volume 9. Radiation Therapy Physics And Treatment Optimization; Volume 10. Physical Medicine And Rehabilitation	Anders Brahme (ed.)	2014	Elsevier Science & Technology Books
932 Objective Functions for Filter Optimization		Microstrip filters for RF microwave applications	Jia-Sheng Hong, M. J. Lancaster	2001	John Wiley and Sons
Meta-Learning for Black-Box Optimization	Vishnu TV; Pankaj Malhotra; Jyoti Narwariya; Lovekesh Vig; Gautam Shroff	Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2019, Würzburg, Germany, September 16–20, 2019, Proceedings, Part II	Ulf Brefeld; Elisa Fromont; Andreas Hotho; Arno Knobbe; Marloes Maathuis; Céline Robardet	1st ed. 2020	Springer International Publishing
Multiple Objective Path Optimization for Time Dependent Objective Functions	Michael M. Kostreva; Laura Lancaster	Multiple Objective and Goal Programming: Recent Developments	Tadeusz Trzaskalik; Jerzy Michnik	2002	Physica-Verlag HD
Optimization with Increasing Objective Functions	Alexander J. Zaslavski	Optimization on Metric and Normed Spaces	Alexander J. Zaslavski	2010	Springer New York
42 Multiobjective Optimization: Objective Functions		Artificial Intelligence in Wireless Communications (Mobile Communications)	Thomas W. Rondeau, Charles W. Bostian	2009	Artech House Publishers
A Model for Analyzing Black-Box Optimization	Vinhthuy Phan; Steven Skiena; Pavel Sumazin	Algorithms and Data Structures: 8th International Workshop, WADS 2003, Ottawa, Ontario, Canada, July 30 - August 1, 2003, Proceedings	Frank Dehne; Jörg Rüdiger Sack; Michiel Smid	2003	Springer Berlin Heidelberg
Parallel Triangulated Partitioning for Black Box Optimization	Yong Wu; Linet Özdamar; Arun Kumar	Global Optimization: Scientific and Engineering Case Studies	János D. Pintér	2006	Springer US
Traditional and Hybrid Derivative-Free Optimization Approaches for Black Box Functions	Genetha Anne Gray; Kathleen R. Fowler	Computational Optimization, Methods and Algorithms	Slawomir Koziel; Xin-She Yang	2011	Springer Berlin Heidelberg
Traditional and Hybrid Derivative-Free Optimization Approaches for Black Box Functions		Computational Optimization, Methods andAlgorithms	Slawomir Koziel, Xin-SheYang (Eds.)	2011	Springer
On Test Functions for Evolutionary Multi-objective Optimization	Tatsuya Okabe; Yaochu Jin; Markus Olhofer; Bernhard Sendhoff	Parallel Problem Solving from Nature - PPSN VIII: 8th International Conference, Birmingham, UK, September 18-22, 2004, Proceedings	Xin Yao; Edmund Burke; Jose A. Lozano; Jim Smith; Juan J. Merelo-Guervós; John A. Bullinaria; Jonathan Rowe; Peter Tino; Ata Kabán; Hans-Paul Schwefel	2004	Springer Berlin Heidelberg
Are Humans Bayesian in the Optimization of Black-Box Functions?	Antonio Candelieri; Riccardo Perego; Ilaria Giordani; Francesco Archetti	Numerical Computations: Theory and Algorithms: Third International Conference, NUMTA 2019, Crotone, Italy, June 15–21, 2019, Revised Selected Papers, Part II	Yaroslav D. Sergeyev; Dmitri E. Kvasov	1st ed. 2020	Springer International Publishing
Optimization Problems with Differentiable Objective Functions		Convex Optimization - Introductory Course	Mikhail Moklyachuk	2021	John Wiley & Sons
Online Black-Box Algorithm Portfolios for Continuous Optimization	Petr Baudiš; Petr Pošík	Parallel Problem Solving from Nature -- PPSN XIII: 13th International Conference, Ljubljana, Slovenia, September 13-17, 2014, Proceedings	Thomas Bartz-Beielstein; Juergen Branke; Bogdan Filipič; James Smith	2014	Springer International Publishing
Features for Exploiting Black-Box Optimization Problem Structure	Tinus Abell; Yuri Malitsky; Kevin Tierney	Learning and Intelligent Optimization: 7th International Conference, LION 7, Catania, Italy, January 7-11, 2013, Revised Selected Papers	Giuseppe Nicosia; Panos Pardalos	2013	Springer Berlin Heidelberg
Complexity Theory for Discrete Black-Box Optimization Heuristics	Carola Doerr	Theory of Evolutionary Computation: Recent Developments in Discrete Optimization	Benjamin Doerr; Frank Neumann	1st ed. 2020	Springer International Publishing
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