Optimization Problems#

Optimization problems expose typed bounds, solver-independent constraints, and problem-specific representative baseline solve() implementations.

The smooth continuous packaged benchmarks in this family continue to use SciPy baselines.

See Optimization Problem Catalog for the generated per-problem catalog pages. For deeper battery-model details and equations, see Battery Ladder Technical Notes.

The packaged entries include:

  • The canonical battery pack compatibility matrix and the meaning of native, projected, and promoted live in Battery Ladder Technical Notes.

  • battery_18650_t1_rectangular_surrogate_opt, a tier-1 rectangular sizing benchmark with a fixed rectangular series-parallel representation and analytic_surrogate, explicit_circuit, or hybrid_thermal scoring.

  • battery_18650_t2_pose_surrogate_opt, a tier-2 pose-aware layout benchmark that adds per-cell [x_mm, y_mm, z_mm, angle_x_deg, angle_y_deg, angle_z_deg] freedom while supporting analytic_surrogate, promoted explicit_circuit, and promoted hybrid_thermal evaluation.

  • battery_18650_t3a_topology_explicit_2rc_opt, a manifest-backed tier-3A backend-config example that defaults to projected explicit_circuit evaluation with the shared pybamm_ecm_2rc battery backend.

  • battery_18650_t3a_topology_surrogate_opt, a tier-3A topology-allocation benchmark that adds active-cell count plus stage assignment and supports analytic_surrogate, projected explicit_circuit, and promoted hybrid_thermal evaluation modes.

  • battery_18650_t3b_netlist_explicit_opt, a tier-3B explicit-netlist benchmark that exposes open-ended transition-program design variables and supports native explicit_circuit and promoted hybrid_thermal scoring.

  • battery_18650_t4_thermal_hybrid_2rc_opt, a manifest-backed tier-4 backend-config example that keeps hybrid_thermal scoring while selecting the shared pybamm_ecm_2rc battery backend.

  • battery_18650_t4_thermal_hybrid_opt, a tier-4 thermal-topology benchmark that adds cooling-system variables and supports analytic_surrogate, explicit_circuit, and hybrid_thermal evaluator modes.

  • battery_fast_charge_dfn_anchor_opt, a PyBaMM DFN-based electrochemical anchor benchmark whose packaged solve() method is a deterministic baseline/reference search rather than a claim of strong optimization.

  • gmpb_default_dynamic_min, a stateful dynamic wrapper that negates the native Generalized Moving Peaks Benchmark maximization score to fit this package’s minimization-oriented optimization API.

  • planar_truss_span_mass_min, a fixed-joint binary planar-truss problem that minimizes structural mass under hard factor-of-safety and deflection limits.

  • planar_truss_span_deflection_min, a fixed-joint binary planar-truss problem that minimizes structural deflection under hard factor-of-safety and mass limits.

  • planar_truss_span_fos_max, a fixed-joint binary planar-truss problem that maximizes factor of safety under hard mass and deflection limits.

  • space_truss_span_mass_min, a fixed-joint binary 3D space-truss problem that minimizes structural mass under hard factor-of-safety and deflection limits.

  • pill_capsule_min_area, a compact nonlinear constrained problem with two continuous variables.

  • moneymaker_hip_pump_cost_min, a citation-backed scalarized cost minimization benchmark derived from the MoneyMaker Hip Pump studies.

  • treadle_pump_ide_material_min, a citation-backed scalarized material minimization benchmark derived from the IDE-style treadle pump studies.