Petri Net Induced Heuristic Search for Resource Constrained Scheduling

Fuente: arXiv
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Hauptverfasser: Lublin, Ido, Atzmon, Dor, Cohen, Izack
Format: Preprint
Veröffentlicht: 2026
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author Lublin, Ido
Atzmon, Dor
Cohen, Izack
author_facet Lublin, Ido
Atzmon, Dor
Cohen, Izack
contents We formulate the Resource-Constrained Project Scheduling Problem (RCPSP) as optimal search over the reachability graph of a Timed Transition Petri Net with Resources, using relative-delay tokens so that scheduling decisions correspond to transition firings in the induced state space. We solve the resulting problem with $A^*$ guided by a heuristic that combines Critical Path and resource-based lower bounds, and prove that it is consistent under our token-based time semantics. Experiments on the PSPLIB benchmarks show that the approach outperforms strong exact Mixed-Integer Linear Programming (MIP) baselines (SCIP, CBC) in both success rate and solve time. Per-instance analysis shows that heuristic search and MIP degrade along independent axes, resource tightness for $A^*$ and formulation size for MIP, with resource strength mediating which solver benefits from scale.
format Preprint
id arxiv_https___arxiv_org_abs_2605_15983
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Petri Net Induced Heuristic Search for Resource Constrained Scheduling
Lublin, Ido
Atzmon, Dor
Cohen, Izack
Artificial Intelligence
We formulate the Resource-Constrained Project Scheduling Problem (RCPSP) as optimal search over the reachability graph of a Timed Transition Petri Net with Resources, using relative-delay tokens so that scheduling decisions correspond to transition firings in the induced state space. We solve the resulting problem with $A^*$ guided by a heuristic that combines Critical Path and resource-based lower bounds, and prove that it is consistent under our token-based time semantics. Experiments on the PSPLIB benchmarks show that the approach outperforms strong exact Mixed-Integer Linear Programming (MIP) baselines (SCIP, CBC) in both success rate and solve time. Per-instance analysis shows that heuristic search and MIP degrade along independent axes, resource tightness for $A^*$ and formulation size for MIP, with resource strength mediating which solver benefits from scale.
title Petri Net Induced Heuristic Search for Resource Constrained Scheduling
topic Artificial Intelligence
url https://arxiv.org/abs/2605.15983