Partial-Order Reduction for Performance Analysis of Max-Plus Timed Systems

Sanden, Bram van der; Geilen, Marc; Reniers, Michel A.; Basten, Twan

doi:10.1109/acsd.2018.00007

Cited by 5 publications

(3 citation statements)

References 18 publications

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“…The property that equivalent runs have the same throughput and latency values was stated in [8] without proof. It is included here with proof for completeness purposes.…”

Section: M])mentioning

confidence: 99%

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Partial-Order Reduction for Supervisory Controller Synthesis

Sanden

Geilen

Reniers

et al. 2022

IEEE Trans. Automat. Contr.

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A key challenge in the synthesis and subsequent analysis of supervisory controllers is the impact of state-space explosion caused by concurrency. The main bottleneck is often the memory needed to store the composition of plant and requirement automata and the resulting supervisor. Partial-order reduction (POR) is a well-established technique that alleviates this issue in the field of model checking. It does so by exploiting redundancy in the model with respect to the properties of interest. For controller synthesis, the functional properties of interest are nonblockingness, controllability, and leastrestrictiveness, but also performance properties, such as throughput and latency are of interest. We propose an on-the-fly POR on the input model that preserves both functional and performance properties in the synthesized supervisory controller. This improves the scalability of the synthesis (and any subsequent performance analysis). Synthesis experiments show the effectiveness of the POR on a set of realistic manufacturing system models.

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“…The property that equivalent runs have the same throughput and latency values was stated in [8] without proof. It is included here with proof for completeness purposes.…”

Section: M])mentioning

confidence: 99%

“…The proposed POR extends the POR introduced in [8] for the performance analysis of timed systems. We consider controller synthesis and the preservation of both functional and performance properties during synthesis.…”

mentioning

confidence: 94%

Partial-Order Reduction for Supervisory Controller Synthesis

Sanden

Geilen

Reniers

et al. 2022

IEEE Trans. Automat. Contr.

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“…Such an on-the-fly approach would avoid the explicit construction of the state-space and optimization-space of a logistics automaton. Furthermore, partial-order reduction techniques, such as the one proposed in Reference [20], could be applied to avoid the exploration of redundant sequences. Another interesting research direction would be the generalization of this algebra and its application to finite-state automata.…”

Section: :25mentioning

confidence: 99%

Taming the State-space Explosion in the Makespan Optimization of Flexible Manufacturing Systems

Bastos

Voeten

Stuijk

et al. 2021

ACM Trans. Cyber-Phys. Syst.

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This article presents a modular automaton-based framework to specify flexible manufacturing systems and to optimize the makespan of product batches. The Batch Makespan Optimization (BMO) problem is NP-Hard and optimization can therefore take prohibitively long, depending on the size of the state-space induced by the specification. To tame the state-space explosion problem, we develop an algebra based on automata equivalence and inclusion relations that consider both behavior and structure. The algebra allows us to systematically relate the languages induced by the automata, their state-space sizes, and their solutions to the BMO problem. Further, we introduce a novel constraint-based approach to systematically prune the state-space based on the the notions of nonpermutation-repulsiveness and permutation-attractiveness. We prove that constraining a nonpermutation-repulsing automaton with a permutation-attracting constraint always reduces the state-space. This approach allows us to (i) compute optimal solutions of the BMO problem when the (additional) constraints are taken into account and (ii) compute bounds for the (original) BMO problem (without using the constraints). We demonstrate the effectiveness of our approach by optimizing an industrial wafer handling controller.

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