Conference proceeding
Scheduling deep-space network data transmissions: a Lagrangian relaxation approach
Proceedings of SPIE, Vol.1963(1), pp.330-340
Applications of Artificial Intelligence 1993: Knowledge-Based Systems in Aerospace and Industry
03/23/1993
DOI: 10.1117/12.141750
Abstract
For various projects (satellites) one must schedule transmissions to receiving antennas on earth for a one week planning horizon. Periods of time in which any satellite is `in view' of any antenna are known in advance. The scheduling problem is formulated as an integer linear program. This formulation includes a large number of non-conflict constraints stating that an antenna must not receive data from two or more satellites simultaneously. There are also a smaller number of service level constraints specif)ed by project managers to assure appropriate levels of service. For example, service level constraints might specify for a particular project: a maximum allowable gap between the end of one transmission and the start of the next, a minimum total number of minutes of transmission during a week, a minimum number of transmissions on any day, etc. Lagrangian Relaxation allows service level constraints to be relaxed (temporarily ignored). These constraints are replaced by economic penalties for not satisfying them. The resulting modified scheduling problem is easily solved. The paper concentrates on formulation, solution by Lagrangian Relaxation, and performance on an example using real data for a week in 1996.
Details
- Title: Subtitle
- Scheduling deep-space network data transmissions: a Lagrangian relaxation approach
- Creators
- Colin E Bell - University of Iowa
- Resource Type
- Conference proceeding
- Publication Details
- Proceedings of SPIE, Vol.1963(1), pp.330-340
- Conference
- Applications of Artificial Intelligence 1993: Knowledge-Based Systems in Aerospace and Industry
- DOI
- 10.1117/12.141750
- ISSN
- 0277-786X
- eISSN
- 1996-756X
- Number of pages
- 11
- Language
- English
- Date published
- 03/23/1993
- Academic Unit
- Business Analytics
- Record Identifier
- 9984962892102771
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