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High-performance technique for satellite range scheduling

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TLDR
The main highlight of the technique is its dual functions of quickly generating a high-quality solution and providing a good bound, which is significantly better than the best-known heuristic.
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This article is published in Computers & Operations Research.The article was published on 2017-09-01. It has received 33 citations till now. The article focuses on the topics: Fair-share scheduling & Dynamic priority scheduling.

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Citations
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Journal ArticleDOI

A mixed integer linear programming model for multi-satellite scheduling

TL;DR: In this paper, a mixed-integer linear programming model is proposed to solve the multi-satellite scheduling problem with limited observation capacities, where constraints are derived from a careful analysis of the interdependency between feasible time intervals that are eligible for observations.
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MOEA based memetic algorithms for multi-objective satellite range scheduling problem

TL;DR: In this article, a general MOEA based memetic algorithm (MOEA-MA) framework is proposed, which optimizes the failure rate of ground-satellite communication requests and the load-balance degree of remote-tracking antennas.
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Priority-based and conflict-avoidance heuristics for multi-satellite scheduling

TL;DR: A two-stage heuristic method is developed to obtain high quality solutions in a reasonable amount of computation time and results reveal that the new proposed methods routinely delivered very close to optimal solutions.
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Optimisation problems and resolution methods in satellite scheduling and space-craft operation: a survey

TL;DR: The fast development in the production of small, low-cost satellites is propelling an important increase in satellite mission planning and operations projects, according to the International Telecommunication Union (ITU).
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Learning-guided nondominated sorting genetic algorithm II for multi-objective satellite range scheduling problem

TL;DR: An improved multi-objective evolutionary algorithm (MOEA) is proposed, called learning-guided nondominated sorting genetic algorithm II (LGNSGAII) that contains a learning mechanism that can speed up optimization process.
References
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Journal ArticleDOI

Three Scheduling Algorithms Applied to the Earth Observing Systems Domain

TL;DR: A fast and simple priority dispatch method is described and shown to produce acceptable schedules most of the time and a look ahead algorithm is introduced that outperforms the dispatcher by about 12% with only a small increase in run time.
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Approximating the Throughput of Multiple Machines in Real-Time Scheduling

TL;DR: This work considers the following fundamental scheduling problem, and gives constant factor approximation algorithms for four variants of the problem, depending on the type of the machines and the weight of the jobs (identical vs. arbitrary).
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Scheduling Space–Ground Communications for the Air Force Satellite Control Network

TL;DR: The first coupled formal and empirical analysis of the Satellite Range Scheduling application is presented, showing that the simplified version of the problem is equivalent to a well-known machine scheduling problem and it is proved that Satelliterange Scheduling is NP-complete.
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A graph coloring heuristic using partial solutions and a reactive tabu scheme

TL;DR: A reactive tabu tenure is introduced which substantially enhances the performance of both the heuristic as well as the classical tabu algorithm proposed by Hertz and de Werra and is found to be one of the most efficient simple local search coloring methods yet available.
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Graph colouring approaches for a satellite range scheduling problem

TL;DR: Numerical experiments showed that the proposed heuristics for the MuRRSP are very competitive, robust, and outperform algorithms based on the permutation solution space.
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