A new single model and derived algorithms for the satellite shot planning problem using graph theory concepts (original) (raw)
Related papers
European Journal of Operational Research, 2002
We consider a satellite following orbits around the earth in order to take shots corresponding to images requested by various customers. The daily operations of such a satellite consist of defining a feasible and satisfactory shot sequence. This problem involves both combinatorial and multiple criteria difficulties. Indeed, the number of feasible shot sequences grows significantly with the number of images asked for, and the evaluation of a shot sequence is based on several conflicting criteria. We propose to formulate this problem as the selection of a multiple criteria path in a graph without circuit. Our approach for solving this problem involves two stages: generation of efficient paths and selection of a satisfactory path using a multiple criteria interactive procedure. Ó
Computational Optimization and Applications, 2010
The problem of managing an Agile Earth Observing Satellite consists of selecting and scheduling a subset of photographs among a set of candidate ones that satisfy imperative constraints and maximize a gain function. We propose a tabu search algorithm to solve this NP-hard problem. This one is formulated as a constrained optimization problem and involves stereoscopic and time window visibility constraints; and a convex evaluation function that increases its hardness. To obtain a wide-ranging and an efficient exploration of the search space, we sample it by consistent and saturated configurations. Our algorithm is also hybridized with a systematic search that uses partial enumerations. To increase the solution quality, we introduce and solve a secondary problem; the minimization of the sum of the transition durations between the acquisitions. Upper bounds are also calculated by a dynamic programming algorithm on a relaxed problem. The obtained results show the efficiency of our approach.
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.
Mathematical Problems in Engineering, 2017
Satellite task planning not only plans the observation tasks to collect images of the earth surface, but also schedules the transmission tasks to download images to the ground station for users’ using, which plays an important role in improving the efficiency of the satellite observation system. However, most of the work to our knowledge, scheduling the observation and transmission tasks separately, ignores the correlation between them in resource (e.g., energy and memory) consumption and acquisition. In this paper, we study the single-satellite observation and transmission task planning problem under a more accurate resource usage model. Two preprocessing strategies including graph partition and nondominated subpaths selection are used to decompose the problem, and an improved label-setting algorithm with the lower bound cutting strategy is proposed to maximize the total benefit. Finally, we compare the proposed method with other three algorithms based on three data sets, and the e...
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.
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...
Novel concept of satellite manoeuvre planning using graph theoretical techniques
Advances in Space Research, 2020
Manoeuvrable, responsive satellite constellations that respond to real time events could provide data on demand for time-critical tasks, such as disaster monitoring and relief efforts. The authors demonstrate the feasibility of such a system by expanding on a fully analytical method for designing responsive spacecraft manoeuvres using low thrust propulsion. These manoeuvres are perceived as a graph that enables efficient exploration and optimised selection of favourable routes that achieve mission goals while highlighting resilience and redundancy in the mission's execution. A case study is presented that considers four satellites required to provide flyovers of two targets, with an associated graph of 10839 possible manoeuvres. Investigation of the graph highlights that a good, but not minimum time, solution can allow the system to perform well, while also providing greater resilience to changes in mission priorities and errors in execution. This analytical approach enables operators to trade-off between a loss of time by using only one satellite versus the disruption of moving multiple satellites for a potentially faster response. The impact of varying mission capabilities, such as using fewer satellites, smaller swath width or less propellant, can be evaluated by reducing the graph without recalculating manoeuvre options.
Upper Bounds for the SPOT 5 Daily Photograph Scheduling Problem
Journal of Combinatorial Optimization, 2003
This paper introduces tight upper bounds for the daily photograph scheduling problem of earth observation satellites. These bounds, which were unavailable until now, allow us to assess the quality of the heuristic solutions obtained previously. These bounds are obtained with a partition-based approach following the "divide and pas conquer" principle. Dynamic programming and tabu search are conjointly used in this
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.
A Constraint-Based Approach to Satellite Scheduling
2001
Satellite scheduling, like all scheduling, is the problem of mapping tasks (observation, communication, downlink, control maneuvers, etc.) to resources (sensor satellites, relay satellites, ground stations, etc.). Through our work on satellite scheduling problems, we have encountered many different constraints that are particular to the satellite-scheduling domain. In this paper, we will introduce the satellite mission-operation scheduling problem, describing the problem constraints that are particular to satellite scheduling, and then present the constraint-based techniques that we have used to address these problems.