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A Lagrangian heuristic for satellite range scheduling with resource constraints

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TLDR
A Lagrangian version of the Fix-and-Relax MIP heuristic is developed which is shown to be equivalent to a sequence of maximum weighted independent set problems on interval graphs, providing near optimal solutions to relevant large scale test problems.
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This article is published in Computers & Operations Research.The article was published on 2011-11-01 and is currently open access. It has received 137 citations till now. The article focuses on the topics: Lagrangian relaxation & Integer programming.

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Citations
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Journal ArticleDOI

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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Collaborative Data Downloading by Using Inter-Satellite Links in LEO Satellite Networks

TL;DR: This paper proposes a collaborative scheme that allows satellites to offload data among themselves using inter-satellite links (ISLs) before they come into contact with the ES, such that satellites will carry the right amount of data according to the length of their contact time with theES and the throughput of data downloading at the ES is maximized.
Journal ArticleDOI

An adaptive large neighborhood search metaheuristic for agile satellite scheduling with time-dependent transition time

TL;DR: A metaheuristic, called adaptive large neighborhood search (ALNS), is developed, thus creating a conflict-free observational timeline, and time slacks are introduced to confine the propagation of the time-dependent constraint of transition time.
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Multi-satellite control resource scheduling based on ant colony optimization

TL;DR: The experiment results demonstrate that the global exploration ability and solution quality of the MSCRSP-ACO is superior to existed algorithms such as genetic algorithm, iterative repair algorithm and max-min ant system.
Journal ArticleDOI

Optimization-based scheduling for the single-satellite, multi-ground station communication problem

TL;DR: The goal in this research is to develop tools that yield high-quality schedules in a timely fashion while accurately modeling on-board satellite energy and data dynamics as well as realistic constraints of the space environment and ground network.
References
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Book

Nonlinear Programming

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Integer programming

TL;DR: The principles of integer programming are directed toward finding solutions to problems from the fields of economic planning, engineering design, and combinatorial optimization as mentioned in this paper, which is a standard of graduate-level courses since 1972.
Book

Modern heuristic techniques for combinatorial problems

TL;DR: In this paper, the Lagrangian relaxation and dual ascent tree search were used to solve the graph bisection problem and the graph partition problem, and the traveling salesman problem scheduling problems.
Journal ArticleDOI

Selected Topics in Column Generation

TL;DR: The growing understanding of the dual point of view is emphasized, which has brought considerable progress to the column generation theory and practice, and is an ever recurring concept in "selected topics."
Journal ArticleDOI

Exploring relaxation induced neighborhoods to improve MIP solutions

TL;DR: Two new approaches to exploring interesting, domain-independent neighborhoods in MIP are considered, the more effective of the two, which is called Relaxation Induced Neighborhood Search (RINS), constructs a promising neighborhood using information contained in the continuous relaxation of the MIP model.
Related Papers (5)
Frequently Asked Questions (10)
Q1. What have the authors contributed in "A lagrangian heuristic for satellite range scheduling with resource constraints" ?

The authors report on their experience in the design of an optimization-based support tool at the European Space Agency. The authors propose a tight time-indexed formulation of the problem able to include several complex technological constraints. 

The authors also wish to thank Alessandro Donati from ESA for his helpful comments during the development of the project. 

In case of Lagrangian relaxation, feasible schedules are typically obtained from pseudoschedules computed during the subgradient optimization by a combination of elementary moves such as swap, insertion, deletion, merge of pseudo-schedule, etc. (see, for instance, [1], [15]). 

Remark that, if satellites have infinite capacity and wj = 1 for all j ∈ J (i.e., all the services have the same revenue), then Srsp-rc-rel boils down to MuRRS. 

Among them, the relaxation in which the assignment (2) and the ground station capacity constraints (3) are dualized shows two important advantages: it has the minimum number of multipliers and, at the same time, yields an efficiently solvable lagrangian subproblem. 

In general, fix-and-relax heuristics can have an important drawback: if at some iteration the relaxed MIP becomes infeasible, nothing can be inferred on the whole problem. 

the set of variables to be fixed is determined exploiting the pseudo-schedule SC derived from the solution of the Lagrangian dual, as explained in the next subsection. 

the Fix-and-Relax scheme cannot be directly applied to {0, 1}- Srsp-rc-rel because even its linear relaxation (see §6) is too difficult to be solved. 

From a mathematical point of view, it is worthwhile to look also at the relaxation of Srsp-rc obtained eliminating precedence, set-up and on-board storage constraints. 

This is becoming a critical task since the rapid increase in the number of satellites cannot be counterbalanced by installing additional, very expensive, ground-stations.