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chips-n-salsa

Chips-n-Salsa is a Java library of customizable, hybridizable, iterative, parallel, stochastic, and self-adaptive local search algorithms. The library includes implementations of several stochastic local search algorithms, including simulated annealing, hill climbers, as well as constructive search algorithms such as stochastic sampling. Chips-n-Salsa now also includes genetic algorithms as well as evolutionary algorithms more generally. The library very extensively supports simulated annealing. It includes several classes for representing solutions to a variety of optimization problems. For example, the library includes a BitVector class that implements vectors of bits, as well as classes for representing solutions to problems where we are searching for an optimal vector of integers or reals. For each of the built-in representations, the library provides the most common mutation operators for generating random neighbors of candidate solutions, as well as common crossover operators for use with evolutionary algorithms. Additionally, the library provides extensive support for permutation optimization problems, including implementations of many different mutation operators for permutations, and utilizing the efficiently implemented Permutation class of the JavaPermutationTools (JPT) library. Chips-n-Salsa is customizable, making extensive use of Java's generic types, enabling using the library to optimize other types of representations beyond what is provided in the library. It is hybridizable, providing support for integrating multiple forms of local search (e.g., using a hill climber on a solution generated by simulated annealing), creating hybrid mutation operators (e.g., local search using multiple mutation operators), as well as support for running more than one type of search for the same problem concurrently using multiple threads as a form of algorithm portfolio. Chips-n-Salsa is iterative, with support for multistart metaheuristics, including implementations of several restart schedules for varying the run lengths across the restarts. It also supports parallel execution of multiple instances of the same, or different, stochastic local search algorithms for an instance of a problem to accelerate the search process. The library supports self-adaptive search in a variety of ways, such as including implementations of adaptive annealing schedules for simulated annealing, such as the Modified Lam schedule, implementations of the simpler annealing schedules but which self-tune the initial temperature and other parameters, and restart schedules that adapt to run length.
https://chips-n-salsa.cicirello.org/
GPL-3.0-or-later
Cicirello.Org
Vincent A Cicirello
Aggregated version Version Update time
6.4 6.4.0 Jul 29, 2023
6.3 6.3.0 May 16, 2023
6.2 6.2.1 Jan 21, 2023
6.2.0 Jan 11, 2023
6.1 6.1.0 Nov 18, 2022
6.0 6.0.0 Sep 03, 2022
5.2 5.2.0 Aug 02, 2022
5.1 5.1.0 Jul 30, 2022
5.0 5.0.1 Jul 26, 2022
5.0.0 Jun 04, 2022
4.8 4.8.0 Jun 02, 2022
4.7 4.7.0 Mar 17, 2022
4.6 4.6.0 Mar 15, 2022
4.5 4.5.0 Feb 23, 2022
4.4 4.4.0 Feb 14, 2022
4.3 4.3.0 Feb 12, 2022
4.2 4.2.1 Jan 28, 2022
4.2.0 Jan 24, 2022
4.1 4.1.0 Jan 14, 2022
4.0 4.0.0 Jan 06, 2022
3.1 3.1.0 Dec 22, 2021
3.0 3.0.0 Oct 26, 2021
2.13 2.13.0 Sep 17, 2021
2.12 2.12.1 Jul 31, 2021
2.12.0 Jul 29, 2021
2.11 2.11.1 May 14, 2021
2.11.0 May 12, 2021
2.10 2.10.0 Mar 27, 2021
2.9 2.9.0 Mar 21, 2021
2.8 2.8.0 Mar 06, 2021
2.7 2.7.0 Feb 25, 2021
2.6 2.6.0 Jan 26, 2021
2.5 2.5.2 Nov 12, 2020
2.5.1 Nov 06, 2020
2.5.0 Nov 03, 2020
2.4 2.4.1 Oct 16, 2020
2.4.0 Oct 16, 2020
2.3 2.3.0 Oct 13, 2020
2.2 2.2.0 Sep 25, 2020
2.1 2.1.0 Sep 19, 2020
41 Records