Download JAR files tagged by solver with all dependencies

Mixed Integer Linear Programming (MILP) solver lp_solve solves pure linear, (mixed) integer/binary, semi-cont and special ordered sets (SOS) models.lp_solve is written in ANSI C and can be compiled on many different platforms like Linux and WINDOWS.

Timefold solves planning problems. This lightweight, embeddable planning engine implements powerful and scalable algorithms to optimize business resource scheduling and planning. Activate JSON-B bindings for Timefold's Score classes. This module is deprecated and will be removed in a future major version of Timefold Solver. Please use the Jackson integration instead.

Timefold solves planning problems. This lightweight, embeddable planning engine implements powerful and scalable algorithms to optimize business resource scheduling and planning. Quarkus integration tests for Timefold with JSON-B. This module is deprecated and will be removed in a future major version of Timefold Solver. Please use the Jackson integration instead.

Timefold solves planning problems. This lightweight, embeddable planning engine implements powerful and scalable algorithms to optimize business resource scheduling and planning. Quarkus deployment module for timefold-solver-quarkus-jsonb. This module is deprecated and will be removed in a future major version of Timefold Solver. Please use the Jackson integration instead.

The Interactive Bin Packing Application provides a self-guided tutorial on combinatorial optimization, the bin packing problem, and constructive heuristics for bin packing. It also enables the user to interact with bin packing instances to explore their own problem solving strategies, or to test their knowledge of the various constructive heuristics covered by the tutorial. The application is not a solver for bin packing. The Interactive Bin Packing Application is a tool for learning about the bin packing problem, as well as for learning about heuristic techniques for solving instances of the problem.

Implements the stochastic variant of the Pegasos (Primal Estimated sub-GrAdient SOlver for SVM) method of Shalev-Shwartz et al. (2007). This implementation globally replaces all missing values and transforms nominal attributes into binary ones. It also normalizes all attributes, so the coefficients in the output are based on the normalized data. Can either minimize the hinge loss (SVM) or log loss (logistic regression). For more information, see S. Shalev-Shwartz, Y. Singer, N. Srebro: Pegasos: Primal Estimated sub-GrAdient SOlver for SVM. In: 24th International Conference on MachineLearning, 807-814, 2007.

Janet Sudoku is a powerful Sudoku Generator and Sudoku Solver library for Java (since jdk 1.5) Android .NET (since 2.0) MONO CLS compliant. Additionally library delivers Janet Sudoku Demo App implementation in a simple form of command line tool, yet highly functional. 1. Sudoku Generator - generate Sudoku puzzles using variety of different methods. 2. Sudoku Solver - Solve any Sudoku puzzle, get the path leading to the correct solution. Check whether unique solution exists. Find all solutions if more than one present. Analyse many built-in examples of Sudoku puzzles or load any other. 3. Manipulate the board by applying transformations not affecting solution existence (i.e. rotation, reflection, permutation, swapping segments, and others). Interact with the library via consisted and well documented API. 4. Janet Sudoku Demo App - use simple, yet highly functional, command line tool to generate, solve evaluate different puzzles.