Models and algorithms for simple disjunctive temporal problems
- URL: http://arxiv.org/abs/2302.02644v1
- Date: Mon, 6 Feb 2023 09:40:24 GMT
- Title: Models and algorithms for simple disjunctive temporal problems
- Authors: Carlo S. Sartori, Pieter Smet, Greet Vanden Berghe
- Abstract summary: We focus on the case where events may have an arbitrarily large number of release and due dates.
We provide three mathematical models to describe this problem using constraint programming and linear programming.
We implement algorithms from the literature and provide the first in-depth empirical study comparing methods to solve simple disjunctive temporal problems.
- Score: 0.8793721044482611
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Simple temporal problems represent a powerful class of models capable of
describing the temporal relations between events that arise in many real-world
applications such as logistics, robot planning and management systems. The
classic simple temporal problem permits each event to have only a single
release and due date. In this paper, we focus on the case where events may have
an arbitrarily large number of release and due dates. This type of problem,
however, has been referred to by various names. In order to simplify and
standardize nomenclatures, we introduce the name Simple Disjunctive Temporal
Problem. We provide three mathematical models to describe this problem using
constraint programming and linear programming. To efficiently solve simple
disjunctive temporal problems, we design two new algorithms inspired by
previous research, both of which exploit the problem's structure to
significantly reduce their space complexity. Additionally, we implement
algorithms from the literature and provide the first in-depth empirical study
comparing methods to solve simple disjunctive temporal problems across a wide
range of experiments. Our analysis and conclusions offer guidance for future
researchers and practitioners when tackling similar temporal constraint
problems in new applications. All results, source code and instances are made
publicly available to further assist future research.
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