Algorithms for propagating resource constraints in AI planning and scheduling: Existing approaches and new results

Laborie, Philippe

doi:10.1016/s0004-3702(02)00362-4

Cited by 178 publications

(117 citation statements)

References 10 publications

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“…There are many variations of the constraints above , as well as further filtering techniques such as the balance constraint (Laborie (2003)). The reader is pointed to Baptiste et al (2001), Laborie (2003) for further details on inference techniques for constraint-based scheduling, and the dissertation of Vilím (2007) for details and improvements to unary resource filtering techniques in particular.…”

Section: Traditional Constraint Programming Approach ("Heavy Model")mentioning

confidence: 99%

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Solving Variants of the Job Shop Scheduling Problem Through Conflict-Directed Search

Grimes

Hébrard

2015

INFORMS Journal on Computing

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We introduce a simple technique for disjunctive machine scheduling problems and show that this method can match or even outperform state of the art algorithms on a number of problem types. Our approach combines a number of generic search techniques such as restarts, adaptive heuristics and solution guided branching on a simple model based on a decomposition of disjunctive constraints and on the reification of these disjuncts. This paper describes the method and its application to variants of the job shop scheduling problem (JSP ).We show that our method can easily be adapted to handle additional side constraints and different objective functions, often outperforming the state of the art and closing a number of open problems.* Moreover, we perform in-depth analysis of the various factors that makes this approach efficient. We show that, while most of the factors give moderate benefits, the variable and value ordering components are key.

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Section: Traditional Constraint Programming Approach ("Heavy Model")mentioning

confidence: 99%

“…The reader is pointed to Baptiste et al (2001), Laborie (2003) for further details on inference techniques for constraint-based scheduling, and the dissertation of Vilím (2007) for details and improvements to unary resource filtering techniques in particular.…”

Section: Traditional Constraint Programming Approach ("Heavy Model")mentioning

confidence: 99%

Solving Variants of the Job Shop Scheduling Problem Through Conflict-Directed Search

Grimes

Hébrard

2015

INFORMS Journal on Computing

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“…We also concentrate on design of new filtering algorithms for integrated planning and scheduling. Traditional scheduling constraints like edge-finders does not work there because the domains of time variables are not tighten so edge finding cannot deduce information about batch ordering [9]. In Visopt, we use a new group of constraints based on batch ordering propagated through the resources (details are out of scope of this paper).…”

Section: Results and Conclusionmentioning

confidence: 99%

Visopt ShopFloor: On the Edge of Planning and Scheduling

Barták

2002

Lecture Notes in Computer Science

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Abstract. Visopt ShopFloor is a complete system for solving real-life scheduling problems in complex industries. In particular, the system is intended to problem areas where traditional scheduling methods failed. In the paper we describe the heart of the Visopt system, a generic scheduling engine. This engine goes beyond traditional scheduling by offering some planning capabilities. We achieved this integrated behaviour by applying Constraint Logic Programming in a less standard way -the definition of a constraint model is dynamic and introduction of constraints interleaves with search.

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“…The transfer policy of the CDMS may lead to data loss when an experiment produces more data than its memory can store and its priority is not high enough to allow a transfer to the mass-memory. This is modeled within MOST using RESERVOIR constraints [5]. Data-producing activities fill the reservoir, while multiple pre-defined data transfer tasks of variable duration empty it.…”

Section: Introductionmentioning

confidence: 99%

Scheduling Scientific Experiments on the Rosetta/Philae Mission

Simonin

Artigues

Hébrard

et al. 2012

Lecture Notes in Computer Science

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Abstract. The Rosetta/Philae mission was launched in 2004 by the European Space Agency (ESA). It is scheduled to reach the comet 67P /ChuryumovGerasimenko in 2014 after traveling more than six billion kilometers. The Philae module will then be separated from the orbiter (Rosetta) to attempt the first ever landing on the surface of a comet. If it succeeds, it will engage a sequence of scientific exploratory experiments on the comet. In this paper we describe a constraint programming model for scheduling the different experiments of the mission. A feasible plan must satisfy a number of constraints induced by energetic resources, precedence relations on activities, or incompatibility between instruments. Moreover, a very important aspect is related to the transfer (to the orbiter then to Earth) of all the data produced by the instruments. The capacity of inboard memories and the limitation of transfers within visibility windows between lander and orbiter, make the transfer policy implemented on the lander's CPU prone to data loss. We introduce a global constraint to handle data transfers. The goal of this constraint is to ensure that data-producing activities are scheduled in such a way that no data is lost. Thanks to this constraint and to the filtering rules we propose, mission control engineers are now able to compute feasible plans in a few seconds for scenarios where minutes or even hours were previously often required. Moreover, in many cases, data transfers are now much more accurately simulated, thus increasing the reliability of the plans.

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Algorithms for propagating resource constraints in AI planning and scheduling: Existing approaches and new results

Cited by 178 publications

References 10 publications

Solving Variants of the Job Shop Scheduling Problem Through Conflict-Directed Search

Solving Variants of the Job Shop Scheduling Problem Through Conflict-Directed Search

Visopt ShopFloor: On the Edge of Planning and Scheduling

Scheduling Scientific Experiments on the Rosetta/Philae Mission

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