pm4py.analysis.solve_marking_equation#

pm4py.analysis.solve_marking_equation(petri_net: PetriNet, initial_marking: Marking, final_marking: Marking, cost_function: Dict[Transition, float] = None) → float[source]#

Solves the marking equation of a Petri net using an Integer Linear Programming (ILP) approach. An optional transition-based cost function can be provided to minimize the solution.

Parameters:

  • petri_net (PetriNet) – The Petri net.

  • initial_marking (Marking) – The initial marking of the Petri net.

  • final_marking (Marking) – The final marking of the Petri net.

  • cost_function – (Optional) A dictionary mapping transitions to their associated costs. If not provided, a default cost of 1 is assigned to each transition.

Returns:

The heuristic value obtained by solving the marking equation.

Return type:

float

import pm4py

net, im, fm = pm4py.read_pnml('model.pnml')
heuristic = pm4py.solve_marking_equation(net, im, fm)
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