Designing maximally permissive deadlock avoidance policies for sequential resource allocation systems through classification theory

Nazeem, Ahmed; Reveliotis, Spyros

doi:10.1109/case.2011.6042400

Cited by 17 publications

(55 citation statements)

References 9 publications

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“…analysis is presented in [38], where it is also shown that the Boolean function of the second layer can be replaced by alternative forms than the one suggested above, with potential gains in the compactness of the classifier and/or the computational effort for its design. Furthermore, the work of [10] provides additional algorithms for the design of the Boolean classifiers of the DNF form that was described above.…”

Section: Complete Parametric Classifiers For the Optimal Dapmentioning

confidence: 99%

“…This affinity has motivated the heuristic of [44] that was mentioned above, and it is further exploited in [11], where an alternative method for the computation of the minimal linear classifier is proposed, based on set-covering concepts and techniques that are borrowed from combinatorial optimization theory [45]. In the next section, we shall return to the identified affinity between the considered problem and the set covering problem, in order to develop the conditions that characterize the existence of a linear classifier for the representation of the maximally permissive DAP of any given RAS instance Φ.…”

Section: State Space Enumeration Classificationmentioning

confidence: 99%

“…Non-Boundary State Removal Figure 6.4: The workflow proposed in [44] for the construction of a minimal linear classifier implementing the maximally permissive DAP of any given RAS Φ (provided that this policy is amenable to such an implementation).…”

Section: State Space Enumeration Classificationmentioning

confidence: 99%

“…Table 6.2 demonstrates the application of the workflow of Figure 6.4 for the optimal linear-classifier design, and concretizes further the concepts and the results that were discussed in the previous paragraphs, by applying this workflow to the design of an optimal linear classifier for the RAS that abstracts the buffer space allocation taking place in the manufacturing system of Figure 6.1. Furthermore, the application of the MIP formulation of [44] upon the sets P(S rs ) and P(S b rs ) of Table 6.2 returned a minimal linear classifier for these two sets -and by means of Technical Result 3, for the entire sets S rs and S b rs -which consists Table 6.2: The various sets obtained by the application of the data-thinning process of Figure 6.4 to the sets S rs and S rs corresponding to the reachable safe and unsafe subspaces of the RAS that abstracts the buffer space allocation taking place in the manufacturing system of Figure …”

Section: State Space Enumeration Classificationmentioning

confidence: 99%

“…9 The last step in the workflow of Figure 6.4 -i.e., the synthesis of the sought classifier -can be formulated and solved as a mixed integer program (MIP); we refer to [44] for the relevant details. The same work also provides an efficient heuristic that can be applied in the cases that the proposed MIP is intractable; in particular, it is shown that the (structural) sub-optimality of the classifier that is returned by this heuristic is bounded by a factor of ln |P(S b rs )|.…”

Section: State Space Enumeration Classificationmentioning

confidence: 99%

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Deadlock Avoidance Policies for Automated Manufacturing Systems Using Finite State Automata

Reveliotis¹,

Nazeem²

2014

Industrial Information Technology

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This chapter considers the problem of deadlock avoidance in flexibly automated manufacturing systems, one of the most prevalent supervisory control problems that challenges the effective deployment of these environments. The problem is addressed through the modeling abstraction of the (sequential) resource allocation system (RAS), and the pursued analysis uses concepts and results from the formal modeling framework of finite state automata (FSA). A notion of optimality is defined through the notion of maximal permissiveness, but the computation of the optimal DAP is shown to be NP-Hard. Hence, the last part of the chapter discusses some approaches that have been developed by the relevant research community in its effort to deal with this negative complexity result. IntroductionContemporary manufacturing is characterized by (i) an ever increasing emphasis on automation and by (ii) a quest for broader product lines and more customized product offerings [22].Indeed, since the beginning of the industrial revolution, automation has been at the core of the mass-production concept and practices, enabling activities and tasks that frequently transcend the human element in terms of capability, consistency, durability and speed [21]. More recently, automation has also been advocated as a key enabler for controlling the overall production cost, especially in economies where labor cost is particularly high. Hence, there is an increasing tendency to confine the presence of the human element on the production shop-floor to supervisory and maintenance tasks only, while the actual production activity is taken over by "intelligent" hardware, materialized in the form of numerically controlled (NC) machines, CHAPTER 6. 2 robots, and other material handling equipment. Clearly, enabling the reliable deployment of such an extensive mode of automation is a pretty challenging task. Yet, in the recent years, things have been further complicated, and the aforementioned challenges have been further exacerbated, by the second manufacturing trend mentioned above, i.e., the emphasis that is placed by the global markets upon choice and customization. This trend implies a need to support the production of a broader set of items, in smaller batch sizes, and with shorter life spans. Such demand and production patterns negate the economies of scale and the efficiencies of the dedicated production lines that have been sought by traditional manufacturing, and (re-)places the emphasis on concepts like resource sharing, flexibility, reconfigurability and concurrency [18]. But the current reality has also shown that the effective support of these concepts on the manufacturing shop-floor is highly non-trivial, and it adds an entirely new layer of complexity and challenges to the aforementioned endeavors towards the automated operation of production systems. The manufacturing world has become increasingly conscious of the fact that the successful design and deployment of flexibly automated production systems necessitates the development of a (ma...

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Section: Complete Parametric Classifiers For the Optimal Dapmentioning

confidence: 99%

Section: State Space Enumeration Classificationmentioning

confidence: 99%

Section: State Space Enumeration Classificationmentioning

confidence: 99%

Section: State Space Enumeration Classificationmentioning

confidence: 99%

Section: State Space Enumeration Classificationmentioning

confidence: 99%

See 3 more Smart Citations

Deadlock Avoidance Policies for Automated Manufacturing Systems Using Finite State Automata

Reveliotis¹,

Nazeem²

2014

Industrial Information Technology

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Real-time management of complex resource allocation systems: Necessity, achievements and further challenges

Reveliotis

2016

Annual Reviews in Control

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Many contemporary applications, ranging from flexibly automated production systems, to automated material handling and intelligent transportation systems, to internet-based workflow management systems, and more recently, to the massively parallelized software systems that emerge in the context of the novel multi-core computing architectures, can be perceived as a set of finite resources that support a number of concurrently running processes. These processes execute in a staged manner and, at each stage, they vie for the allocation of various subsets of the system resources. To effectively support and manage the extensive levels of concurrency and operational flexibility that are contemplated for these environments, and the ensuing complexity, there is a substantial need for formal models and tools that will enable the modeling, analysis and eventually the control of the aforementioned resource allocation function so that the resulting dynamics are, both, behaviorally correct and operationally efficient. This article overviews a research program that seeks to address the aforementioned need by using the unifying abstraction of the resource allocation system (RAS) and supporting modeling frameworks, like automata, Petri nets, and Markov reward and decision processes, borrowed from the area of Discrete Event Systems (DES) theory. The presented results take advantage of the special structure that exists in the considered RAS classes, and they are characterized by their analytical rigor and computational tractability. The article also highlights the further challenges that must be addressed for the successful completion and promotion of the pursued framework.

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Time based deadlock prevention for Petri nets

et al. 2022

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Designing maximally permissive deadlock avoidance policies for sequential resource allocation systems through classification theory

Cited by 17 publications

References 9 publications

Deadlock Avoidance Policies for Automated Manufacturing Systems Using Finite State Automata

Deadlock Avoidance Policies for Automated Manufacturing Systems Using Finite State Automata

Real-time management of complex resource allocation systems: Necessity, achievements and further challenges

Time based deadlock prevention for Petri nets

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