New tabu search heuristic in scheduling earth observation satellites (original) (raw)
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Aerospace Science and Technology, 2013
Resources scheduling in Low Earth Orbit (LEO) satellites is an important optimization problem because of the satellites' specific constraints. This article addresses a scheduling problem for LEO satellites missions to assign resources which could be satellites or ground stations to the most number of requested tasks by considering the tasks' priority and satisfying temporal and resource constraints. In this study, first, the scheduling problem is modeled using the graph coloring theory. Then, a new tabu search (TS) algorithm is applied to solve the problem. The proposed algorithm employs a new move function to enhance the exploration ability. Accordingly, an attempt is made to compare the result of the proposed TS with some well-known optimization algorithms. The computational results denote the efficiency of the proposed algorithm, as well as its ability to find schedules that are guaranteed to be near-optimal.
Heuristic Scheduling Algorithm Oriented Dynamic Tasks for Imaging Satellites
Mathematical Problems in Engineering, 2014
Imaging satellite scheduling is an NP-hard problem with many complex constraints. This paper researches the scheduling problem for dynamic tasks oriented to some emergency cases. After the dynamic properties of satellite scheduling were analyzed, the optimization model is proposed in this paper. Based on the model, two heuristic algorithms are proposed to solve the problem. The first heuristic algorithm arranges new tasks by inserting or deleting them, then inserting them repeatedly according to the priority from low to high, which is named IDI algorithm. The second one called ISDR adopts four steps: insert directly, insert by shifting, insert by deleting, and reinsert the tasks deleted. Moreover, two heuristic factors, congestion degree of a time window and the overlapping degree of a task, are employed to improve the algorithm’s performance. Finally, a case is given to test the algorithms. The results show that the IDI algorithm is better than ISDR from the running time point of v...
Planning and scheduling for fleets of earth observing satellites
Proceedings of the 6th …, 2002
We address the problem of scheduling observations for a collection of earth observing satellites. This scheduling task is a difficult optimization problem, potentially involving many satellites, hundreds of requests, constraints on when and how to service each request, and resources such as instruments, recording devices, transmitters, and ground stations. High-fidelity models are required to ensure the validity of schedules; at the same time, the size and complexity of the problem makes it unlikely that systematic optimization search methods will be able to solve them in a reasonable time. This paper presents a constraint-based approach to solving the EOS scheduling problem, and proposes a stochastic heuristic search method for solving it.
In this paper, we propose a method that uses a genetic algorithm for the dynamic schedule optimization of imaging missions for multiple satellites and ground systems. In particular, the visibility conflicts of communication and mission operation using satellite resources (electric power and onboard memory) are integrated in sequence. Resource consumption and restoration are considered in the optimization process. Image acquisition is an essential part of satellite missions and is performed via a series of subtasks such as command uplink, image capturing, image storing, and image downlink. An objective function for optimization is designed to maximize the usability by considering the following components: user-assigned priority, resource consumption, and image-acquisition time. For the simulation, a series of hypothetical imaging missions are allocated to a multisatellite control system comprising five satellites and three ground stations having S-and X-band antennas. To demonstrate the performance of the proposed method, simulations are performed via three operation modes: general, commercial, and tactical.
A Tabu Search Algorithm for Ground Station Scheduling Problem
2014 IEEE 28th International Conference on Advanced Information Networking and Applications, 2014
Mission planning plays an important role in satellite control systems. Satellites are not autonomously operated in many cases but are controlled by tele-commands transmitted from ground stations. Therefore, mission scheduling is crucial to efficient satellite control systems, especially with increase of number of satellites and more complex missions to be planned. In a general setting, the satellite mission scheduling consists in allocating tasks such as observation, communication, etc. to resources (spacecrafts (SCs), satellites, ground stations). One common version of this problem is that of ground station scheduling, in which the aim is to compute an optimal planning of communications between satellites and operations teams of Ground Station (GS). Because the communication between SCs and GSs can be done during specific window times, this problem can also be seen as a window time scheduling problem. The required communication time is usually quite smaller than the window of visibility of SCs to GSs, however, clashes are produced, making the problem highly constrained. In this paper we present a Tabu Search (TS) algorithm for the problem, while considering several objective functions, namely, windows fitness, clashes fitness, time requirement fitness, and resource usage fitness. The proposed algorithm is evaluated by a set of problem instances of varying size and complexity generated with the STK simulation toolkit. The computational results showed the efficacy of TS for solving the problem on all considered objectives.
Mission planning and scheduling for Earth observation space system
Mission planning and scheduling for Earth observation space system, 2020
Planning and scheduling systems are needed to manage Earth-observing satellites for satisfying the optimum usage of the constellation's resources. This is a combinatorial optimization NP-hard problem that is solved in this paper using the constraint programming technique. The proposed system can deal with a heterogeneous constellation that consists of satellites with different maneuverability, placed in different orbits, and loaded with different payloads. The system's user can choose one of six optimization objectives, three of them were not used before, for constructing the satellites' mission plan. Searching within the system is performed using one of five different search algorithms. The system produces plans with different planning horizons ranging from one track to more than one month. The obtained results depict that the proposed system behaves, comparatively, in a perfect manner even when dealing with a complicated case study consisting of three satellites, 2,500 targets, and a one-month planning horizon.
2007
Earth observation satellites are platforms equipped with optical instruments that orbit the Earth in order to take photographs of specific areas at the request of users. This article is concerned with the management of several satellites performing multiple orbits over a given planning horizon. It describes a tabu search heuristic for the problem of selecting and scheduling the requests to be satisfied, under operational constraints. An upper bounding procedure based on column generation is used to evaluate the quality of the solutions. The results of extensive computational experiments performed on data provided by the French Centre National d'Études Spatiales are reported.
Computational Optimization and Applications - COMPUT OPTIM APPL, 2001
The daily photograph scheduling problem of earth observation satellites such as Spot 5 consists of scheduling a subset of mono or stereo photographs from a given set of candidates to different cameras. The scheduling must maximize a profit function while satisfying a large number of constraints. In this paper, we first present a formulation of the problem as a generalized version of the well-known knapsack model, which includes large numbers of binary and ternary “logical” constraints. We then develop a tabu search algorithm which integrates some important features including an efficient neighborhood, a dynamic tabu tenure mechanism, techniques for constraint handling, intensification and diversification. Extensive experiments on a set of large and realistic benchmark instances show the effectiveness of this approach.
Multi-objective optimization for multi-satellite scheduling task
Journal of Soft Computing Exploration
The satellites scheduling mission play an effective role in enhancing the role of ground station control and monitoring systems. In this search, SGSEO is re-formulated into a multi-objective optimization task. Therefore, the Gravitational Search Algorithm GSA is exploited to attain several essential objectives for generating tight scheduling. Moreover, particle swarm optimization model PSO is consolidated with GSA in a novel form for strengthening its ability of local search and slow the speed of convergence. On the other side, to make the most of the satellite resources in the right direction, we have observed targets that have fewer observational opportunities to keep them from being lost. The PageRank algorithm is used to fulfil this issue by ranking the candidate's strips. Finally, the effect of different parameters of the proposed approach was studied by experimental outcomes and compared with previous methods. It has shown that the performance of the proposed approach is s...
Planning and Scheduling of Earth Observing Satellites
2007 IEEE Aerospace Conference, 2007
The roles and interactions of activity planning and scheduling for Earth Observing Satellites are based on factors such as mission objective, system assets and resources, system and spacecraft constraints, planning criteria, scheduling strategies, timelines, and desired level of automation and operator interaction. Activities are generalized into four categories: accomplish the mission objective, support the mission objective, manage the system resources,