Scheduling Optimization Solver OptSeq
Fast solving of large-scale scheduling optimization.
OptSeq is a general-purpose scheduling optimization solver specialized in scheduling optimization. It allows for the description of various practical constraints and employs algorithms specifically designed for scheduling optimization problems, enabling it to produce good solutions in a short time for large-scale scheduling optimization problems that cannot be solved by mathematical optimization solvers. In OptSeq, while considering 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, it is a solver capable of addressing due date minimization scheduling and mixed scheduling of forward and backward scheduling. Features: It allows for modeling 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 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
