Everything about Backtracking line search

🧭 Start here: a 6-step reading path

1. Read the overview: Backtracking line searchA 5-minute orientation
2. Skim a recent paper: Looking For Novelty in Search-Based Software Product Line TestingInfluential work since 2022
3. Pick up a classic book: Teaching and training for on-line work in librariesThe most-reprinted book on the subject
4. Read the landmark paper: On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programmingCited 8,525 times
5. Go sideways: Gradient descentA closely related topic
6. Go sideways: Wolfe conditionsA closely related topic

🏆 Landmark papers (most cited)

• On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming

  Andreas Wächter, Lorenz T. Biegler · 2005 · Mathematical Programming · 8,525 citations

• PRESS Peer Review of Electronic Search Strategies: 2015 Guideline Statement

  Jessie McGowan, Margaret Sampson, Douglas M. Salzwedel · 2016 · Journal of Clinical Epidemiology · 4,967 citations

• Depth-First Search and Linear Graph Algorithms

  Robert Tarjan · 1972 · SIAM Journal on Computing · 4,770 citations

• Line search algorithms with guaranteed sufficient decrease

  Jorge J. Moré, David J. Thuente · 1994 · ACM Transactions on Mathematical Software · 411 citations

• On the Nonmonotone Line Search

  Y. H. Dai · 2002 · Journal of Optimization Theory and Applications · 165 citations

• Nonmonotone line search for minimax problems

  J. L. Zhou, A. L. Tits · 1993 · Journal of Optimization Theory and Applications · 103 citations

• Stochastic assembly line balancing using beam search

  E. Erel *, I. Sabuncuoglu, H. Sekerci · 2005 · International Journal of Production Research · 69 citations

• Rendezvous Search on the Line

  Shmuel Gal · 1999 · Operations Research · 68 citations

🆕 Influential since 2022

• Looking For Novelty in Search-Based Software Product Line Testing

  Yi Xiang, Han Huang, Miqing Li · 2022 · IEEE Transactions on Software Engineering · 20 citations

• The miniJPAS survey: A search for extreme emission-line galaxies

  J. Iglesias-Páramo, A. Arroyo, C. Kehrig · 2022 · Astronomy & Astrophysics · 18 citations

• Learned Data-aware Image Representations of Line Charts for Similarity Search

  Yuyu Luo, Yihui Zhou, Nan Tang · 2023 · Proceedings of the ACM on Management of Data · 17 citations

• Adaptive Clustering Quasi-Line Search Path Planning Algorithm Based On Sampling

  Yifei Zhang, Zihao Zhang, Shiyuan Wang · 2023 · IEEE Transactions on Vehicular Technology · 16 citations

• Globally linearly convergent nonlinear conjugate gradients without Wolfe line search

  Arnold Neumaier, Morteza Kimiaei, Behzad Azmi · 2024 · Numerical Algorithms · 12 citations

📚 Books worth reading

• 📕Teaching and training for on-line work in librariesAldyth D. Scott · 1979
• Online bibliographic databasesJames Logan Hall, Marjorie J. Brown · 1981
• The future of the catalogS. Michael Malinconico · 1979
• 📕The use of ISBNs compared with keywords as means of retrieving bibliographic records on-lineAnthony G. Curwen · 1980
• 📕Patents databasesOnline Information Centre. · 1982
• 📕An overview of British Library funded projects on the use of online search services by five English public libraries, January 1980-September 1981Lucy A. Tedd · 1982
• 📕Training requirements for online intermediariesStella Keenan · 1982
• 📕Third on-line education workshopFrances E. Wood · 1979

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

🔗 Related topics

• Gradient descent Gradient descent is a method for unconstrained mathematical optimization. It is a first-order iterative algorithm for minimizing a differentiable multivariate…
• Wolfe conditions In the unconstrained minimization problem, the Wolfe conditions (also known as the Armijo-Wolfe conditions in some books) are a set of inequalities for…
• Newton's method in optimization In calculus, Newton's method (also called Newton–Raphson) is an iterative method for finding the roots of a differentiable function f, which are solutions…
• Stochastic gradient descent Stochastic gradient descent (often abbreviated SGD) is an iterative method for optimizing an objective function with suitable smoothness properties (e…
• Gauss–Newton algorithm In numerical methods, the Gauss–Newton algorithm is an iterative algorithm to solve non-linear least squares problems. It is an extension of Newton's method…
• Subgradient method Subgradient methods are convex optimization methods which use subderivatives. Originally developed by Naum Z. Shor and others in the 1960s and 1970s, subgradien…
• Line search In optimization, line search is a basic iterative approach to find a local minimum 𝐱∗ of an objective function f:ℝn→ℝ. It first finds a descent direction…
• Steffensen's method In numerical analysis, Steffensen's method is an iterative method named after Johan Frederik Steffensen for numerical root-finding that is similar to the…