Reactive scheduling framework based on domain knowledge and constraint programming

Novas, Juan M.; Henning, Gabriela P.

doi:10.1016/j.compchemeng.2010.07.011

Cited by 59 publications

(35 citation statements)

References 22 publications

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“…Thus, the online framework utilizing a model had to be tailored to that specific model, and required many ad-hoc (heuristic) adjustments to be able to represent and resolve a disturbance to the schedule [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23]. The introduction of the state-space idea to chemical production scheduling alleviated many of these issues that arose from having to make ad-hoc adjustments [24].…”

Section: Introductionmentioning

confidence: 99%

A General State-Space Formulation for Online Scheduling

Gupta

Maravelias

2017

Processes

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Abstract:We present a generalized state-space model formulation particularly motivated by an online scheduling perspective, which allows modeling (1) task-delays and unit breakdowns; (2) fractional delays and unit downtimes, when using discrete-time grid; (3) variable batch-sizes; (4) robust scheduling through the use of conservative yield estimates and processing times; (5) feedback on task-yield estimates before the task finishes; (6) task termination during its execution; (7) post-production storage of material in unit; and (8) unit capacity degradation and maintenance. Through these proposed generalizations, we enable a natural way to handle routinely encountered disturbances and a rich set of corresponding counter-decisions. Thereby, greatly simplifying and extending the possible application of mathematical programming based online scheduling solutions to diverse application settings. Finally, we demonstrate the effectiveness of this model on a case study from the field of bio-manufacturing.

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Section: Introductionmentioning

confidence: 99%

A General State-Space Formulation for Online Scheduling

Gupta

Maravelias

2017

Processes

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“…CP effectiveness when addressing scheduling problems have been proved by many contributions in different domains, such as manufacturing scheduling [22], train scheduling [23], batch plant scheduling [20] and [24], staff scheduling [25], assembly lines scheduling [26], etc. However, future research in CP requires being oriented towards its integration within other technologies, as part of enterprise service-oriented framework.…”

Section: The Cp Scheduling Systemmentioning

confidence: 99%

“…Further details about the CP modeling are out of the scope of this work. Constraint programming-based scheduling formulations for flow shop environments can be found, for instance in [20], [32] and [33].…”

Section: Fig 4 Manufacturing Plant Configurationmentioning

confidence: 99%

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A Collaborative Framework between a Scheduling System and a Holonic Manufacturing Execution System

Novas

Belle

Germain

et al. 2013

Service Orientation in Holonic and Multi Agent Manufacturing and Robotics

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Abstract. This paper presents developments on a collaborative framework between a centralized manufacturing scheduling system (SS) and a decentralized manufacturing execution system (MES). The paper intends to integrate such systems with the aim of reducing the existing gap between detailed manufacturing scheduling systems and lower level systems, like MESs. Moreover, the framework exploits the benefits of each specialized technology and complements their capabilities in order to collaborate at runtime. The SS is based on constraint programming (CP) technology, while the holonic MES or HMES implements the PROSA reference architecture and applies the delegate multiagent system pattern (D-MAS). The scheduling system generates a good quality schedule, which execution is performed by the HMES. In turn, the HMES requires services from the SS in order to update the schedule. The paper also shows the impact that disruptive events have on the execution performance. Experimental results have shown a trade-off between efficiency and stability metrics.

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“…However, little information has been given about the autonomic decision mechanism. A reactive scheduling framework based on domain knowledge and constraint programming was proposed by Novasand Henning [4]. An explicit object-oriented domain representation and a constraint programming (CP) approach to the model were utilized to the modeling and realizing method when unforeseen event occurs.…”

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confidence: 99%

A Dynamic Rescheduling Model with Multi-Agent System and Its Solution Method

Zhao¹,

Wang²,

Wang³

et al. 2012

SV-JME

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Dynamic rescheduling problem is an important issue in modern manufacturing system with the feature of combinatorial computation complexity. A dynamic rescheduling model, which is based on Multi-Agent System (MAS), INTRODUCTIONToday's manufacturing businesses are facing immense pressures to react rapidly and robustly to dynamic fluctuations in demand distributions across products and changing product mix. Traditional manufacturing systems and approaches to production, involving sequential stages from manufacturing systems design, construct, and setup in the preparation phase to production planning, scheduling, and control in the operational phase, can be challenging in satisfying the requirement of the variation. Efficient and practical methods for scheduling and optimization technology are the key to improve the productivity and efficiency of a manufacturing plant [1]. The traditional scheduling and optimization process, which always deals with a clear schedule and a fixed processing time, while for the actual processing problem, there are many uncertain factors, for example, changes in processing time, product demand, delivery, equipment failure, resources and production variations. The dynamic interference of these factors causes that the original dynamic scheduling can not be implemented successfully. Therefore, the rescheduling model and its solution method are of significant importance for the dynamic scheduling problem [2].Job shop scheduling is to schedule a set of jobs on a set of machines, which is subject to the constraint that each machine can process one job at most at a given time and the fact that each job has a specified processing order through the machines. It is not only a NP-hard problems, it also has the well-earned reputation of being one of the strong combinatorial problems in manufacturing systems. Recently, two single-machine rescheduling problems with linear deteriorating jobs under disruption was studied by Zhao and Tang [3]. Job shop rescheduling problem was being considered as minimizing the total completion time under a limit of the disruption from the original scheduling. However, little information has been given about the autonomic decision mechanism. A reactive scheduling framework based on domain knowledge and constraint programming was proposed by Novasand Henning [4]. An explicit object-oriented domain representation and a constraint programming (CP) approach to the model were utilized to the modeling and realizing method when unforeseen event occurs. A reactive scheduling methodology for job shop, make-to-order industries, by inserting new orders in a predetermined schedule, was introduced to iteratively update the schedules [5]. By applying local rescheduling in response to schedule disruptions was presented to reduce the size of the regarded problems by applying methods of partial rescheduling in literature [6]. Mehta [7] processed the way to absorb the random failure of the disturbance proposed by the appropriate method of inserting new orders in idle time. Kim [8] propos...

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Reactive scheduling framework based on domain knowledge and constraint programming

Cited by 59 publications

References 22 publications

A General State-Space Formulation for Online Scheduling

A General State-Space Formulation for Online Scheduling

A Collaborative Framework between a Scheduling System and a Holonic Manufacturing Execution System

A Dynamic Rescheduling Model with Multi-Agent System and Its Solution Method

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