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dc.contributor.authorXhafa Xhafa, Fatos
dc.contributor.authorHerrero, Xavier
dc.contributor.authorBarolli, Admir
dc.contributor.authorTakizawa, Makoto
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Ciències de la Computació
dc.date.accessioned2017-05-30T10:50:41Z
dc.date.available2017-05-30T10:50:41Z
dc.date.issued2014
dc.identifier.citationXhafa, F., Herrero , X., Barolli, A., Takizawa, M. A comparison study on meta-heuristics for ground station scheduling problem. A: International Conference on Network-Based Information Systems. "2014 International Conference on Network-Based Information Systems, NBiS 2014, 10-12 September 2014, University of Salerno, Salerno, Italy: proceedings". Salerno: Institute of Electrical and Electronics Engineers (IEEE), 2014, p. 172-179.
dc.identifier.isbn978-1-4799-4226-8
dc.identifier.urihttp://hdl.handle.net/2117/105018
dc.description.abstractIn ground station scheduling problem the aim is to compute an optimal planning of communications between Spacecrafts (SCs) and operations teams of Ground Stations (GSs). While such allocation of tasks to ground stations traditionally is mostly done by human intervention, modern scheduling systems look at optimization and automation features. Such features, on the one hand, would increase the efficiency and productivity of the mission planning systems by handling a larger number of missions, achieve a higher usage of the infrastructure (grand stations' antennae) and, on the other, would avoid error-prone human allocation and reduce human labour costs. Designing such modern, automated scheduling/planning systems is however challenging due to the highly constraint and complex nature of the problem seeking to optimize along various objectives or system parameters. In this paper we present a study on the performance of several meta-heuristics methods for solving ground station scheduling problem. Local search methods (Hill Climbing, Simulated Annealing and Tabu Search) and population-based methods (GA, Steady State GA and Struggle GA) have been considered for the study. The performance of these resolution methods was measured by a set of instances of varying size and complexity generated by STK toolkit. The study revealed the strengths and weaknesses of the considered methods while solving different size instances and considering several objective functions, namely, windows fitness, clashes fitness, time requirement fitness, and resource usage fitness.
dc.format.extent8 p.
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Satèl·lits i ràdioenllaços
dc.subject.lcshMathematical optimization
dc.subject.lcshComputer algorithms
dc.subject.lcshSpace vehicles
dc.subject.otherGenetic algorithms
dc.subject.otherGround station scheduling
dc.subject.otherLocal search
dc.subject.otherSTK Satellite Simulation Toolkit
dc.subject.othermission planning
dc.titleA comparison study on meta-heuristics for ground station scheduling problem
dc.typeConference report
dc.subject.lemacOptimització matemàtica
dc.subject.lemacAlgorismes genètics
dc.subject.lemacVehicles espacials
dc.identifier.doi10.1109/NBiS.2014.29
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7023950
dc.rights.accessOpen Access
local.identifier.drac17840301
dc.description.versionPostprint (author's final draft)
local.citation.authorXhafa, F.; Herrero, X.; Barolli, A.; Takizawa, M.
local.citation.contributorInternational Conference on Network-Based Information Systems
local.citation.pubplaceSalerno
local.citation.publicationName2014 International Conference on Network-Based Information Systems, NBiS 2014, 10-12 September 2014, University of Salerno, Salerno, Italy: proceedings
local.citation.startingPage172
local.citation.endingPage179


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