The Online Books Page

Heuristic algorithms

See also what's at your library, or elsewhere.

• Computer algorithms

• Approximation algorithms

• Heuristics (Computer algorithms)

• The Design of Approximation Algorithms (electronic prepublication edition, c2011), by David P. Williamson and David Bernard Shmoys (PDF files with commentary at designofapproxalgs.com)

Items below (if any) are from related and broader terms.

• Matters Computational: Ideas, Algorithms, Source Code (prepublication version, 2011), by Jörg Arndt (PDF and other formats at jjj.de)
• Elements of Programming (authors' edition; 2019), by Alexander A. Stepanov and Paul McJones (PDF files with commentary at elementsofprogramming.com)
• Foundations of Machine Learning (second edition; Cambridge, MA and London: MIT Press, c2018), by Mehryar Mohri, Afshin Rostamizadeh, and Ameet Talwalkar (HTML at ublish.com)
• Machine Learning (main text c1997; additional chapters c2017), by Tom M. Mitchell (PDF with commentary at CMU)
• Open Data Structures (multiple editions; c2013), by Pat Morin
  • Java and C++ editions; PDF files with commentary at opendatastructures.org
  • AU Press edition; PDF with commentary at AU Press
• Clever Algorithms: Nature-Inspired Programming Recipes (c2011), by Jason Brownlee
  • PDF at Github
  • PDF with commentary at Github
• Algorithms and Data Structures (based on the 1985 edition; updated for Oberon in 2004), by Niklaus Wirth (PDF in Switzerland)
• Text Algorithms (electronic edition, 1997), by Maxime Crochemore and Wojciech Rytter (PDF in France)
• Algorithms and Complexity (first edition, 1994), by Herbert S. Wilf (PDF with commentary here at Penn)
• Information, Randomness and Incompleteness (second edition, 1990), by Gregory J. Chaitin (Postscript at Maine)
• Lecture Notes on Bucket Algorithms (1986), by Luc Devroye (PDF at devroye.org)
• Programming Computer Vision with Python (prepublication draft, 2012), by Jan Erik Solem (PDF with commentary at programmingconputervision.com)
• Computer Vision: Algorithms and Applications (prepublication draft, c2010), by Richard Szeliski (PDF with commentary at szeliski.org)
• Combinatorial Algorithms for Computers and Calculators (second edition, c1978), by Albert Nijenhuis and Herbert S. Wilf (PDF with commentary here at Penn)
• Introduction to Data Science: Data Analysis and Prediction Algorithms With R (Creative Commons online edition, 2021), by Rafael A. Irizarry (illustrated HTML with commentary at github.uio)
• Data Structures and Algorithms With Object-Oriented Design Patterns in Java (online version, with links to versions for other languages; c1999), by Bruno R. Preiss (frame-dependent HTML at Wayback Machine)
• Elements of Causal Inference: Foundations and Learning Algorithms (Cambridge, MA and London: MIT Press, c2017), by Jonas Peters, Dominik Janzing, and Bernhard Schölkopf (PDF with commentary at MIT Press)
• Data Structures and Algorithms With Object-Oriented Design Patterns in C++ (online version, with links to versions for other languages; c1999), by Bruno R. Preiss (frame-dependent HTML at Wayback Machine)

• Algorithms (c2019), by Jeff Erickson (PDF files with commentary at Illinois)

• Knowledge Graphs and Big Data Processing (Lecture Notes in Computer Science #12072; Cham: Springer, c2020), ed. by Valentina Janev, Damien Graux, Hajira Jabeen, and Emanuel Sallinger (multiple formats at Springer Link)

• Journal of Graph Algorithms and Applications (1997-) (full serial archives)