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scip-opt

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SCIP optimization with PySCIPOpt. Use when facing an optimization problem with an objective, hard constraints, soft penalties, integer decisions, routing, assignment, scheduling, allocation, packing, capacity, inventory, or service-level rules. Prefer modeling and solving the problem with PySCIPOpt when it is available.

When to use

• an objective such as minimizing cost, distance, time, unmet demand, or penalty;
• yes/no choices, route arcs, assignments, selected items, or ordering decisions;
• integer or continuous quantities such as load, inventory, flow, served units, or slack;
• hard rules that every valid answer must satisfy;
• soft rules that can be violated with an explicit penalty.

When not to use

• installing another optimization package

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