Multicriterial evaluation and optimization of an algorithm for charging energy storage elements

Kishkin, Krasimir; Arnaudov, Dimitar; Todorov, Venelin; Fidanova, Stefka

doi:10.15439/2021f55

Cited by 2 publications

(1 citation statement)

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“…They coped with the size issue by trying to adapt standard column generation and branch and cut techniques (see [7]), but faced difficulties as soon as the size of the time space increased. All those contributions suggested that the Time Expanded Network might be very efficient to deal with scheduling/routing problems involving synchronization (see [15], [14]) requirement or time dependence features (see [20]) .…”

Section: Introductionmentioning

confidence: 99%

Algorithmic Handling of Time Expanded Networks

Quilliot,

Figueroa,

Toussaint

2023

Annals of Computer Science and Information Systems

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Time Expanded Networks, built by considering the nodes of a base network over some time space, are powerful tools for the formulation of problems involving synchronization mechanisms. Those mechanisms may for instance be related to the interaction between resource production and consumption or between routing and scheduling. Still, in most cases, deriving algorithms from those formulations is difficult, due to both the size of resulting network structure and the fact that reducing this size through rounding techniques tends to induce uncontrolled error propagation. We address here this algorithmic issue, while proposing a generic decomposition scheme which works by first skipping the temporal dimension of the problem and next expanding resulting projected solution into a full solution of the problem set on the time expanded network.

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