Everything about Test functions for optimization

🧭 Start here: a 6-step reading path

1. Read the overview: Test functions for optimizationA 5-minute orientation
2. Skim a recent paper: Tree optimization algorithm (TOA): a novel metaheuristic approach for solving mathematical test functions and engineering problemsInfluential work since 2022
3. Pick up a classic book: Software EngineeringThe most-reprinted book on the subject
4. Read the landmark paper: A wide class of test functions for global optimizationCited 56 times
5. Go sideways: Evolutionary multi-objective optimizationA closely related topic
6. Go sideways: Kalyanmoy DebA closely related topic

🏆 Landmark papers (most cited)

• A wide class of test functions for global optimization

  Fabio Schoen · 1993 · Journal of Global Optimization · 56 citations

• A Review of Benchmark and Test Functions for Global Optimization Algorithms and Metaheuristics

  M. Z. Naser, Mohammad Khaled Al‐Bashiti, Arash Teymori Gharah Tapeh · 2025 · WIREs Computational Statistics · 42 citations

• A framework for generating tunable test functions for multimodal optimization

  Jani Rönkkönen, Xiaodong Li, Ville Kyrki · 2010 · Soft Computing · 35 citations

• A new class of test functions for global optimization

  Bernardetta Addis, Marco Locatelli · 2006 · Journal of Global Optimization · 26 citations

• Functions with noise-induced multimodality: a test for evolutionary robust Optimization-properties and performance analysis

  H.-G. Beyer, B. Sendhoff · 2006 · IEEE Transactions on Evolutionary Computation · 25 citations

• Application of Grasshopper Optimization Algorithm for Constrained and Unconstrained Test Functions

  Abhishek G Neve, Ganesh M Kakandikar, Omkar Kulkarni · 2017 · International Journal of Swarm Intelligence and Evolutionary Computation · 24 citations

• A study of test functions for optimization algorithms

  R. Chattopadhyay · 1971 · Journal of Optimization Theory and Applications · 19 citations

• A class of test functions for global optimization

  Rudolf Mathar, Antanas Zilinskas · 1994 · Journal of Global Optimization · 17 citations

🆕 Influential since 2022

• Tree optimization algorithm (TOA): a novel metaheuristic approach for solving mathematical test functions and engineering problems

  M. J. Mahmoodabadi, M. Rasekh, M. Yahyapour · 2022 · Evolutionary Intelligence · 9 citations

• COMBINING GREY WOLF OPTIMIZATION AND WHALE OPTIMIZATION ALGORITHM FOR BENCHMARK TEST FUNCTIONS

  Mustafa Serter UZER, Onur İNAN · 2023 · Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi · 4 citations

• Runge Kutta Optimization for Fixed Size Multimodal Test Functions

  Fatih CANTAŞ, Serdar ÖZYÖN, Celal YAŞAR · 2022 · International Scientific and Vocational Studies Journal · 3 citations

• Correction to “A Review of Benchmark and Test Functions for Global Optimization Algorithms and Metaheuristics”

  · 2025 · WIREs Computational Statistics · 2 citations

• Composite Test Functions for Benchmarking Nonlinear Optimization Software

  János D. Pintér · 2025 · Mathematics · 0 citations

📚 Books worth reading

• Software EngineeringRoger S. Pressman, Bruce Maxim · 1982
• Calculus, Early TranscendentalsJames Stewart · 1991
• Neural Information ProcessingTingwen Huang · 2012
• Clean CodeRobert C. Martin · 2008
• Multivariable Calculus, Concepts and ContextsJames Stewart · 1998
• 📕Pamphlets - homoeopathicThomson, J. W. M.D., Robert N. Tooker · 1844
• Applied biomedical engineering mechanicsDhanjoo N. Ghista · 2008
• System softwareLeland L. Beck · 1985

Ranked by number of editions on Open Library, a rough measure of how lasting a book is.

🔗 Related topics

• Evolutionary multi-objective optimization Evolutionary multi-objective optimization (EMO), also called evolutionary multi-criterion optimization, is the application of evolutionary algorithms to…
• Kalyanmoy Deb Kalyanmoy Deb (born 1963) is an Indian computer scientist. Deb is currently the Endowed Shelby Distinguished Professor in the Department of Computer Science…
• Pareto frontier In multi-objective optimization, the Pareto frontier (also called the Pareto front, Pareto set, Pareto boundary or Pareto curve) is the set of all Pareto…
• Fitness function A fitness function is a particular type of objective or cost function that is used to summarize, as a single figure of merit, how close a given candidate…
• Evolutionary multimodal optimization In applied mathematics, multimodal optimization deals with optimization tasks that involve finding all or most of the multiple (at least locally optimal)…
• Multi-objective optimization In multiple-criteria decision making, multi-objective optimization or Pareto optimization (also known as multi-objective programming, vector optimization…
• Particle swarm optimization In computational science, particle swarm optimization (PSO) is a computational method that optimizes a problem by iteratively trying to improve a population…
• MOEA Framework The MOEA Framework is an open-source evolutionary computation library for Java that specializes in multi-objective optimization. It supports a variety…