Essentials of Metaheuristics

What Hacker News says

1. cchianelDec 2025
   Some additional optimization resources (for metaheuristics, where you only have the objective/score function and no derivative):

   - "Essentials of Metaheuristics" by Sean Luke https://cs.gmu.edu/~sean/book/metaheuristics/

   - "Clever Algorithms" by Jason Brownlee https://cleveralgorithms.com/

   Timefold uses the metaheuristic algorithms in these books (Tabu Search, Late Acceptance, Simulated Annealing, etc.) to find near-optimal solutions quickly from a score function (typically defined in a Java stream-like/SQL-like syntax so score calculation can be done incrementally to improve score calculation speed).

   You can see simplified diagrams of these algorithms in action in Timefold's docs: https://docs.timefold.ai/timefold-solver/latest/optimization....

   Disclosure: I work for Timefold.

   Show morethread
2. HoushalterMar 2017
   More relevant to this is the Essentials of Metaheuristics: https://cs.gmu.edu/~sean/book/metaheuristics/ (There is a free pdf download on that page.)
   thread
3. SeanLukeApr 2012
   The Genetic Algorithm ("genetic algorithms" is actually a misnomer) actually has little to do with biology except for original inspiration. It is simply one of a number of sample-based methods for doing global stochastic optimization.

   There's an old saying about the Genetic Algorithm: that it's the "third best way to do anything". Stochastic optimization methods (or "metaheuristics") in general are knowledge-poor methods, essentially last-ditch techniques where you don't have any other known way to solve your problem and you don't want to jump off the cliff into random or brute-force search. They rely on a central heuristic: that similar candidate solutions will likely have similar performance (the "smoothness" criterion).

   Here's the thing. There are a huge and growing number of crunchy problems in this category. If you're trying to find a good tic-tac-toe solution, you can almost certainly do better than a stochastic optimization method (just use state-space search, say). But if what if you're trying to find the set of behaviors for a two-thousand-agent multiagent simulation model which produces statistics most closely resembling known historical data? Or what if you're trying to find the best parameters for optimizing an aircraft engine whose space is filled with local optima? It's ugly problems like these, for which there is no principled solution method, where the Genetic Algorithm and its ilk reign supreme. You might say that you never see problems in computer science which are "best solved using genetic algorithms". My answer is: your daily problems are too simple to need them.

   Book plug: you might enjoy my free online text on the subject, called Essentials of Metaheuristics. You can also get it in paperback. http://cs.gmu.edu/~sean/book/metaheuristics/

   Show morethread
4. SeanLukeFeb 2012
   Allow me to recommend my own free text, which covers most of the field: Essentials of Metaheuristics. http://cs.gmu.edu/~sean/book/metaheuristics/
   thread
5. jacques_chesterDec 2014
   I got a lot of value from A Field Guide to Genetic Programming[1] and Introduction to Evolutionary Computing[2] when I was studying this stuff.

   I've heard good things about Essentials of Metaheuristics[3] and Clever Algorithms[4] too, I would like to read them some day.

   [1] http://www.gp-field-guide.org.uk/

   [2] http://www.cs.vu.nl/~gusz/ecbook/ecbook.html

   [3] http://cs.gmu.edu/~sean/book/metaheuristics/

   [4] http://www.cleveralgorithms.com/

   Show morethread
6. SeanLukeMar 2013
   I went back and forth with Springer about publishing my book (Essentials of Metaheuristics). It was a completed, edited, typeset, and ready to go volume, and my rep really wanted it, but couldn't convince her higher-ups of the one requirement I had: that I retain copyright on electronic copies. The reason was that I intended to release new versions of the book once every two months or so, constantly modifying and updating the book, and didn't want to go through the hassle of Springer approval for new editions every month.

   This was of course a non-starter. Springer believes that in the coming years it will make nearly all of its money on electronic volumes. Heck, they'd be glad to give me the rights to the bound volumes, but no way will they release the electronic volumes.

   So I put out electronic versions for free and bound volumes for people who want to buy them at minimal cost through Lulu. It's been a moderate success in a very narrow field: maybe about 6000 downloads a year.

   Show morethread