Solving the swath segment selection problem through Lagrangean relaxation

Authors:
Roberto Cordone;Federico Gandellini;Giovanni Righini
Affiliations:
Universití degli Studi di Milano, Dipartimento di Tecnologie dell'Informazione, Via Bramante 65, 26013 Crema, Italy;Universití degli Studi di Milano, Dipartimento di Tecnologie dell'Informazione, Via Bramante 65, 26013 Crema, Italy;Universití degli Studi di Milano, Dipartimento di Tecnologie dell'Informazione, Via Bramante 65, 26013 Crema, Italy
Venue:
Computers and Operations Research
Year:
2008

Citing 3
Cited 0

Knapsack problems: algorithms and computer implementations

Knapsack problems: algorithms and computer implementations
A “Logic-Constrained” Knapsack Formulation and a Tabu Algorithm for the Daily Photograph Scheduling of an Earth Observation Satellite

Computational Optimization and Applications
Three Scheduling Algorithms Applied to the Earth Observing Systems Domain

Management Science

Quantified Score

Hi-index	0.01

Visualization

Abstract

The swath segment selection problem (SSSP) is an -hard combinatorial optimization problem arising in the context of planning and scheduling satellite operations. It was defined by Muraoka et al. [ASTER observation scheduling algorithm. In: Proceedings of SpaceOps 1998, Tokyo, Japan, 1998] and Knight and Smith [Optimal nadir observation scheduling. In: Proceedings of the fourth international workshop on planning and scheduling for space (IWPSS 2004), Darmstadt, Germany, 2004], who respectively proposed a greedy algorithm, named ASTER, and a branch-and-bound algorithm based on a network flow relaxation. Here we tackle the problem with more advanced mathematical programming tools: using a Lagrangean relaxation, coupled with a Lagrangean heuristic and subgradient optimization, we solve in one hour instances with up to 500000 swath segments within 0.4% of the optimum. The algorithm also proves experimentally superior to commercial MIP solvers in computing heuristic solutions.