Developing a Totally Unimodular Linear Program for Optimal Conformance Checking: When and Why It Complements A*
arXiv:2605.26938v1 Announce Type: new Abstract: Alignment-based conformance checking is the state-of-the-art approach for comparing observed process executions with normative process models. The standard exact solution relies on an A*-based heuristic search, which can exhibit exponential runtime in the presence of long traces or substantial deviations. This paper introduces a reformulation of alignment-based conformance checking as a totally unimodular linear program (LP) defined on the reachability graph of the synchronous product. By exploiting the underlying network-flow structure, the prop
The paper introduces a recent advancement in algorithmic efficiency for conformance checking, an established process mining technique, addressing its limitations with large datasets.
Improving the accuracy and scalability of process mining through more efficient algorithms directly impacts the ability of organizations to analyze and optimize complex operational workflows, making AI-powered automation more robust.
The proposed totally unimodular linear program offers an alternative, more robust method for alignment-based conformance checking, potentially reducing computational bottlenecks for certain use cases where A*-based heuristics struggle.
- · Process mining software vendors
- · Organizations with complex operational workflows
- · AI-driven automation platforms
- · Researchers in formal methods and AI
- · Organizations relying solely on less efficient legacy process conformance tools
More accurate and scalable process conformance checks for complex business processes.
Accelerated adoption and effectiveness of AI agents in process automation due to better oversight and verification capabilities.
Enhanced trust and broader deployment of autonomous systems in critical enterprise functions, driven by verifiable process adherence.
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Read at arXiv cs.AI