A Lagrangian heuristic for satellite range scheduling with resource constraints

The data exchange between ground stations and satellite constellations is becoming a challenging task, as more and more communication requests must be daily scheduled on a few, expensive stations located all around the Earth. Most of the scheduling procedures adopted in practice cannot cope with suc...

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Bibliographic Details
Published in:Computers & operations research Vol. 38; no. 11; pp. 1572 - 1583
Main Authors: Marinelli, Fabrizio, Nocella, Salvatore, Rossi, Fabrizio, Smriglio, Stefano
Format: Journal Article
Language:English
Published: Kidlington Elsevier Ltd 01.11.2011
Elsevier
Pergamon Press Inc
Subjects:
Applications
Applied sciences
Communication satellites
Computer science; control theory; systems
Computer systems and distributed systems. User interface
Constellations
Exact sciences and technology
Ground stations
Heuristic
Integer programming
Lagrange multiplier
Lagrangian heuristic
Linear programming
Mathematical analysis
Mathematical models
Mathematical programming
Multiprocessor scheduling
Operational research and scientific management
Operational research. Management science
Optimization
Satellite communications
Satellites
Scheduling
Scheduling, sequencing
Software
Studies
Time-indexed scheduling formulation
Italy
Multiprocessor scheduling
Time-indexed scheduling formulation
Lagrangian heuristic
Applications
Satellite communications
Income
Satellite telecommunication
Temporal databases
Satellite
Time dependence
Lagrange multiplier
Zero one programming
Independent set
Relaxation method
Large scale system
Interval graph
Script
Lagrangian
Task scheduling
Graph theory
Constrained optimization
Integer programming
Processor scheduling
Resource constraint
Optimal solution
Heuristic method
ISSN:0305-0548, 1873-765X, 0305-0548
Online Access:Get full text
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Summary:The data exchange between ground stations and satellite constellations is becoming a challenging task, as more and more communication requests must be daily scheduled on a few, expensive stations located all around the Earth. Most of the scheduling procedures adopted in practice cannot cope with such complexity, and the development of optimization-based tools is strongly spurred. We show that the problem can be formulated as a multiprocessor task scheduling problem in which each job (communication) requires a time dependent pair of resources (ground station and satellite) to be processed, and the objective consists of maximizing the total revenue of on-time jobs. A time-indexed {0,1}-linear programming formulation is then introduced able to include all the complex technological constraints of current constellations. Unfortunately, relevant real-world scenarios yield integer programs with hundreds of thousands variables and a few million constraints, which cannot be tackled by standard integer programming (either exact or heuristic) techniques. To overcome this difficulty, we developed a Lagrangian version of the Fix-and-Relax MIP heuristic. It is based on a Lagrangian relaxation of the problem which is shown to be equivalent to a sequence of maximum weighted independent set problems on interval graphs. The heuristic has been implemented in a tool used by the Italian reference operator for the GALILEO constellation, providing near optimal solutions to relevant large scale test problems.
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ISSN:0305-0548
1873-765X
0305-0548
DOI:10.1016/j.cor.2011.01.016