Satellite downlink scheduling problem: A case study

Abstract

The synthetic aperture radar (SAR) technology enables satellites to efficiently acquire high quality images of the Earth surface. This generates significant communication traffic from the satellite to the ground stations, and, thus, image downlinking often becomes the bottleneck in the efficiency of the whole system. In this paper we address the downlink scheduling problem for Canada's Earth observing SAR satellite, RADARSAT-2. Being an applied problem, downlink scheduling is characterised with a number of constraints that make it difficult not only to optimise the schedule but even to produce a feasible solution. We propose a fast schedule generation procedure that abstracts the problem specific constraints and provides a simple interface to optimisation algorithms. By comparing empirically several standard meta-heuristics applied to the problem, we select the most suitable one and show that it is clearly superior to the approach currently in use.

Perception, reality, and the adoption of business analytics: Evidence from North American professional sport organizations

“…Professional sports teams are using data to drive decisions about player acquisition, development, and in-game tactics in order to gain competitive advantage on the field [13,20,24,42]. This interest extends to the academic world as well.…”

“…The proliferation of analytics by businesses to assess risks and make decisions has been well documented (for recent examples, see [3,28,24,35]; and [33]). The rise of corporate investments in analytics allows management to make more informed decisions [7]; however, there is ambiguity around these investments.…”

A Hybrid Genetic Algorithm for Satellite Image Downlink Scheduling Problem

“…Most of the literature on satellite mission planning is divided into two categories: optical satellites [1][2][3][4] and Synthetic Aperture Radar (SAR) satellites [5][6][7][8][9][10][11][12]. The satellite image acquisition and image downlink are two main scheduling problems in satellite mission planning.…”

“…Downlink also can be classified into two ways: (1) the observed images are transmitted to the ground station in real time when the observation target and the ground station are simultaneously visible to the satellite; (2) first store observed images in the onboard memory and then transmit data to the ground station when the satellite is passing. Discrete Dynamics in Nature and Society SIDSP and its variations have been studied by many authors, mainly divided into single-satellite problems [10][11][12] and multisatellite problems [1,3,[5][6][7][8][9]. Single-satellite problem deals with the resource contention for satellite internal requests, while multisatellite problem should also take the resource contention for requests from different satellites into consideration.…”

“…The solving methods are mainly divided into three categories: (1) exact solution algorithms (e.g., mixed integer programming [13], dynamic programming [14], and branch and bound algorithm [15]); (2) heuristic algorithms (e.g., a priority-based heuristic [3], an ejection-chain heuristic [11], and a Lagrangian heuristic [16]); (3) metaheuristic algorithms (e.g., simulated annealing [12], tabu search [12,17], and genetic algorithm [18]). The performance of these solving methods is measured through the instances with varied size and complexity.…”