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 using solution principles specialized for combinatorial optimization problems, SCOP can efficiently explore good solutions even for large-scale 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 (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
