Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/87108
Title: Temporal plan quality improvement and repair using local search
Authors: Bajada, Josef
Fox, Maria
Long, Derek
Keywords: Scheduling
Mathematical optimization
Algorithms
Issue Date: 2014
Publisher: IOS Press
Citation: Bajada, J., Fox, M., & Long, D. (2014). Temporal plan quality improvement and repair using local search. European Starting AI Researcher Symposium (STAIRS 2014), Prague. 41-50.
Abstract: This paper presents an approach to repair or improve the quality of plans which make use of temporal and numeric constructs. While current stateof- the-art temporal planners are biased towards minimising makespan, the focus of this approach is to maximise plan quality. Local search is used to explore the neighbourhood of an input seed plan and find valid plans of a better quality with respect to the specified cost function. Experiments show that this algorithm is effective to improve plans generated by other planners, or to perform plan repair when the problem definition changes during the execution of a plan.
URI: https://www.um.edu.mt/library/oar/handle/123456789/87108
Appears in Collections:Scholarly Works - FacICTAI

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