2012
DOI: 10.2514/1.51749
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Comparative Analysis of Global Techniques for Performance and Design Optimization of Launchers

Abstract: The main goal of this paper is to analyze different methodologies and to quantitatively compare a set of algorithms for multi-objective global optimization, as an initial step toward a multidisciplinary design optimization framework for space transportation systems. Through a comparative analysis based on mathematical benchmarks, hierarchies among several stochastic techniques are proposed. This leads to the identification of two algorithms as the most promising for multidisciplinary design optimization applic… Show more

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Cited by 15 publications
(12 citation statements)
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“…A previous research work [19] describes in detail the use of such global optimization strategies for the application to trajectory and multidisciplinary designs, including an extensive quantitative comparison on mathematical benchmarks and representative test problems; hence, no further details are reported here. The optimization architecture is completed by a stateof-the-art gradient-based algorithm called WORHP [20], which was developed by the University of Bremen and Universität Würzburg and externally linked to the MDO environment.…”
Section: Mdo Architecture and Optimization Approachmentioning
confidence: 99%
See 1 more Smart Citation
“…A previous research work [19] describes in detail the use of such global optimization strategies for the application to trajectory and multidisciplinary designs, including an extensive quantitative comparison on mathematical benchmarks and representative test problems; hence, no further details are reported here. The optimization architecture is completed by a stateof-the-art gradient-based algorithm called WORHP [20], which was developed by the University of Bremen and Universität Würzburg and externally linked to the MDO environment.…”
Section: Mdo Architecture and Optimization Approachmentioning
confidence: 99%
“…Additional models are included to account for the propulsion performance variation with altitude, in-flight ignitions, and path constraints evaluation (heat flux, axial and lateral accelerations, dynamic pressure, static controllability, and geographic heading). More details about the trajectory models and their validation can be found in [19].…”
Section: F Trajectorymentioning
confidence: 99%
“…32 They are very common in the literature, and are used primarily as exemplars in reference texts, [32][33][34] or in situations when representative values are acceptable in lieu of higher fidelity calculations. 35,36 The strengths and weaknesses of heuristics are generally understood and accepted. While they do not provide the fidelity required to do real design trades, they are well suited to do rough order of magnitude (ROM) calculations, as they provide the fastest and ultimately most flexible of all the modeling techniques.…”
Section: Heuristicmentioning
confidence: 99%
“…• Global Stochastic approach based on Evolutionary Algorithms, with the collaborative hybridization of three different algorithms: Non-Dominated Sorting Genetic Algorithm (NSGA-II) 21 , Double Grid Multi Objective Particle Swarm Optimization (DGMOPSO) 11 , and Multi Objective Ant Colony Optimization for continuous domains (MOACOr) 22 . The idea is to steer the algorithm toward the strategy that achieved the best results, in terms of contribution to the current Pareto Front, in the previous iteration.…”
Section: Global and Local Optimization Algorithmsmentioning
confidence: 99%
“…To tackle this issue, the engineering models have been developed in two successive levels of detail, from conceptual to early-preliminary design. Previous papers [11][12][13] describe in detail models and algorithms introduced for the conceptual level step, and show disciplinary methods and optimization algorithms validation results. The present work draws on this experience, and focuses on a critical analysis of the system design results, with a twofold objective: to assess their accuracy, and to identify the most critical modeling aspects to be improved for the successive early-preliminary design step.…”
Section: Introductionmentioning
confidence: 99%