Constraint Optimization Solver SCOP
Solving large-scale combinatorial optimization problems quickly.
SCOP (Solver for Constraint Programming) is a solver designed to quickly solve large-scale combinatorial optimization problems. By utilizing solution principles specialized for combinatorial optimization problems, SCOP can efficiently explore good solutions even for large problems that traditional mathematical optimization solvers cannot handle. Features: By defining variables in a different way than mathematical optimization solvers, it can significantly reduce the number of variables, enabling fast solutions. It allows for a more natural logical constraint description that is easier for humans to understand compared to mathematical optimization solvers. Based on metaheuristics, it possesses world-class search capabilities. Even for large-scale problems, it can solve them extremely efficiently within limited computation time. It provides data input through a simple modeling language and a Python language interface.
- Company：ログ・オプト
- Price：Other
