NDLI: Energetic reasoning for energy-constrained scheduling with a continuous resource

Content Provider	Springer Nature Link
Author	Artigues, Christian Lopez, Pierre
Copyright Year	2014
Abstract	This paper addresses a scheduling problem with continuous resources and energy constraints. Given a set of non-preemptive activities, each activity requires a continuously divisible resource whose instantaneous usage is limited in maximum and minimum, its processing satisfying a time window and a total energy (time $$\times $$ resource-usage) requirement. The goal consists of getting a schedule satisfying all the constraints. The problem, which we refer to as the Energy-Constrained Scheduling Problem with Continuous Resources (CECSP), is a generalization of the well-known cumulative scheduling problem for which the “energetic reasoning” or “left-shift/right-shift” necessary feasibility condition yielded a popular polynomially computable satisfiability test. The paper presents a generalization of the energetic reasoning for the CECSP, defining precisely the activity minimum consumptions and exhibiting a polynomial number of relevant time intervals on which it is sufficient to apply the satisfiability tests. A strongly polynomial energetic reasoning satisfiability test can be derived for the considered generalization, which also yields a short proof for the complexity of the original algorithm. Some limits of the approach, as well as an approximation framework for more general resource consumption functions, are also addressed.
Starting Page	225
Ending Page	241
Page Count	17
File Format	PDF
ISSN	10946136
Journal	Journal of Scheduling
Volume Number	18
Issue Number	3
e-ISSN	10991425
Language	English
Publisher	Springer US
Publisher Date	2014-12-03
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Scheduling with continuous resources Energy requirement Energetic reasoning satisfiability test Complexity Operations Research/Decision Theory Calculus of Variations and Optimal Control; Optimization Optimization Artificial Intelligence (incl. Robotics) Production/Logistics/Supply Chain
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Management Science and Operations Research Engineering Software

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