Plan Repair Applied to Autonomous Underwater Vehicle Swarms
01 Apr 2019-pp 989-994
TL;DR: This paper presents an application of a new plan repair algorithm proposed recently, the 15-puzzle algorithm with potential with potential to the concrete context of underwater autonomous vehicles mission planning.
Abstract: Plan repair is a field of AI planning which is related to plan execution since it requires the monitoring of the actions to be executed. This paper presents an application of a new plan repair algorithm we proposed recently, the 15-puzzle algorithm with potential [18]–[20] to the concrete context of underwater autonomous vehicles mission planning. In a multi-drone mission in underwater environment, one must repair a plan when a vehicle breaks down. We propose a model for the plan repair problem and show results obtained with our algorithm.
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TL;DR: PDDL2.1 as discussed by the authors is a modelling language capable of expressing temporal and numeric properties of planning domains and has been used in the International Planning Competitions (IPC) since 1998.
Abstract: In recent years research in the planning community has moved increasingly towards application of planners to realistic problems involving both time and many types of resources. For example, interest in planning demonstrated by the space research community has inspired work in observation scheduling, planetary rover exploration and spacecraft control domains. Other temporal and resource-intensive domains including logistics planning, plant control and manufacturing have also helped to focus the community on the modelling and reasoning issues that must be confronted to make planning technology meet the challenges of application.
The International Planning Competitions have acted as an important motivating force behind the progress that has been made in planning since 1998. The third competition (held in 2002) set the planning community the challenge of handling time and numeric resources. This necessitated the development of a modelling language capable of expressing temporal and numeric properties of planning domains. In this paper we describe the language, PDDL2.1, that was used in the competition. We describe the syntax of the language, its formal semantics and the validation of concurrent plans. We observe that PDDL2.1 has considerable modelling power -- exceeding the capabilities of current planning technology -- and presents a number of important challenges to the research community.
1,420 citations
TL;DR: A framework for understanding rescheduling strategies, policies, and methods based on a wide variety of experimental and practical approaches that have been described in the rescheduled literature is described.
Abstract: Many manufacturing facilities generate and update production schedules, which are plans that state when certain controllable activities (e.g., processing of jobs by resources) should take place. Production schedules help managers and supervisors coordinate activities to increase productivity and reduce operating costs. Because a manufacturing system is dynamic and unexpected events occur, rescheduling is necessary to update a production schedule when the state of the manufacturing system makes it infeasible. Rescheduling updates an existing production schedule in response to disruptions or other changes. Though many studies discuss rescheduling, there are no standard definitions or classification of the strategies, policies, and methods presented in the rescheduling literature. This paper presents definitions appropriate for most applications of rescheduling manufacturing systems and describes a framework for understanding rescheduling strategies, policies, and methods. This framework is based on a wide variety of experimental and practical approaches that have been described in the rescheduling literature. The paper also discusses studies that show how rescheduling affects the performance of a manufacturing system, and it concludes with a discussion of how understanding rescheduling can bring closer some aspects of scheduling theory and practice.
818 citations
"Plan Repair Applied to Autonomous U..." refers background in this paper
...[23] published in 2003 a framework for all possible rescheduling strategies (see Table I)....
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...TABLE I Rescheduling framework proposed in [23]....
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TL;DR: A reduction of the set of possible neighbours to a subset for which it can be proved that it always contains the neighbour with the lowest makespan and an efficient approach to compute such a subset of feasible neighbours is presented.
Abstract: The flexible job shop problem is an extension of the classical job shop scheduling problem which allows an operation to be performed by one machine out of a set of machines. The problem is to assign each operation to a machine (routing problem) and to order the operations on the machines (sequencing problem), such that the maximal completion time (makespan) of all operations is minimized. To solve the flexible job shop problem approximately, we use local search techniques and present two neighbourhood functions (Nopt1, Nopt2). Nopt2 is proved to be optimum connected. Nopt1 does not distinguish between routing or sequencing an operation. In both cases, a neighbour of a solution is obtained by moving an operation which affects the makespan. Our main contribution is a reduction of the set of possible neighbours to a subset for which can be proved that it always contains the neighbour with the lowest makespan. An efficient approach to compute such a subset of feasible neighbours is presented. A tabu search procedure is proposed and an extensive computational study is provided. We show that our procedure outperforms previous approaches. Copyright © 2000 John Wiley & Sons, Ltd.
486 citations
"Plan Repair Applied to Autonomous U..." refers background or methods in this paper
...1) Deriving from a tabu search for FJSPs: as we said, our algorithm is derived from [5] which consists in starting from a given initial plan and moving successively some scheduled...
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...The neighborhood for tabu search in [5] has also been associated by G....
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...It is a local search algorithm derived from a classical tabu search approach [5]....
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...[5] proposed a local search approach for FJSP scheduling (FJSP means Flexible Job-Shop scheduling Problem, see Section IV-C3)....
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TL;DR: This paper developed a hybrid genetic algorithm (GA) that uses two vectors to represent solutions and developed an efficient method to find assignable time intervals for the deleted operations based on the concept of earliest and latest event time.
470 citations
"Plan Repair Applied to Autonomous U..." refers methods in this paper
...proposed a hybrid genetic algorithm for the FJSP [6], one of them involving variable neighborhoods [7]....
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TL;DR: Heuristics for the problem of rescheduling a machine on occurrence of an unforeseen disruption are developed and are shown to be effective in that the schedule stability can be increased significantly with little or no sacrifice in makespan.
273 citations