I develop and maintain:
- A solver dedicated to geometrical packing problems fontanf/packingsolver
- Packages that simplify the implementation of combinatorial optimization algorithms based on the following methods:
- Local search fontanf/localsearchsolver (C++) fontanf/localsearchsolverpy (Python3)
- Heuristic tree search fontanf/treesearchsolver (C++) fontanf/treesearchsolverpy (Python3)
- Column generation heuristics fontanf/columngenerationsolver (C++) fontanf/columngenerationsolverpy (Python3)
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Other libraries to simplify the implementation of optimizaztion algorithms:
- Various data structures fontanf/optimizationtools
- Simplify solvers integration with CMake + a simple MILP modeler fontanf/mathoptsolverscmake
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Solvers for various fundamental optimization problems that often appear as subproblems of more complex optimization problems:
- 0-1 knapsack problem, subset-sum problem, multiple-choice subset-sum problem fontanf/knapsacksolver
- Generalized assignment problem fontanf/generalizedassignmentsolver
- (Unicost) set covering problem fontanf/setcoveringsolver
- Maximum(-weight) independent set and maximum-(weight) clique problems fontanf/stablesolver
- Graph coloring problem fontanf/coloringsolver
- Traveling salesman problem fontanf/travelingsalesmansolver
- Some research codes:
- Star observation scheduling problems fontanf/starobservationschedulingsolver
- Travelling thief problems fontanf/travellingthiefsolver
- Flow shop, job shop and open shop scheduling problems fontanf/shopschedulingsolver
Finally, the repository fontanf/teaching contains the material I use to teach.
Do not hesitate to let me know if you use some of my codes. I'm happy to know that they are useful. And I'll be more careful not to break everything in the next update. And do not hesitate to give me some feedback as well.