Scheduling Optimization Solver OptSeq
Rapidly solving large-scale scheduling optimization.
OptSeq is a general-purpose scheduling optimization solver specialized in scheduling optimization. It can describe various practical constraints and uses algorithms tailored for scheduling optimization problems, enabling it to provide good solutions in a short time for large-scale scheduling optimization problems that cannot be solved by mathematical optimization solvers. OptSeq considers renewable resources such as machines and people, non-renewable resources that are consumed such as money and materials, setup times, interruptions during work, resource occupancy and non-occupancy during interruptions, parallel tasks, selection of work modes, and arbitrary time constraints between tasks, allowing it to solve scheduling problems that minimize delays and mixed scheduling of forward and backward scheduling. Features: It allows modeling of scheduling optimization problems in a more natural expression (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 be solved 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
