TY - JOUR
T1 - On the detection of nearly optimal solutions in the context of single-objective space mission design problems
AU - Schütze, O.
AU - Lara, A.
AU - Coello, C. A.C.
AU - Vasile, M.
N1 - Funding Information:
C. A. Coello Coello acknowledges support from CONACyT project no. 128554. Adriana Lara acknowledges support from ESFM-IPN and CONACyT to pursue graduate studies at the Computer Science Department of CINVESTAV-IPN. M. Vasile acknowledges support from CONACyT project no. 103570.
PY - 2011/11
Y1 - 2011/11
N2 - When making decisions, having multiple options available for a possible realization of the same project can be advantageous. One way to increase the number of interesting choices is to consider, in addition to the optimal solution x*, also nearly optimal or approximate solutions; these alternative solutions differ from x* and can be in different regions – in the design space – but fulfil certain proximity to its function value f(x*). The scope of this article is the efficient computation and discretization of the set E of ϵ–approximate solutions for scalar optimization problems. To accomplish this task, two strategies to archive and update the data of the search procedure will be suggested and investigated. To make emphasis on data storage efficiency, a way to manage significant and insignificant parameters is also presented. Further on, differential evolution will be used together with the new archivers for the computation of E. Finally, the behaviour of the archiver, as well as the efficiency of the resulting search procedure, will be demonstrated on some academic functions as well as on three models related to space mission design.
AB - When making decisions, having multiple options available for a possible realization of the same project can be advantageous. One way to increase the number of interesting choices is to consider, in addition to the optimal solution x*, also nearly optimal or approximate solutions; these alternative solutions differ from x* and can be in different regions – in the design space – but fulfil certain proximity to its function value f(x*). The scope of this article is the efficient computation and discretization of the set E of ϵ–approximate solutions for scalar optimization problems. To accomplish this task, two strategies to archive and update the data of the search procedure will be suggested and investigated. To make emphasis on data storage efficiency, a way to manage significant and insignificant parameters is also presented. Further on, differential evolution will be used together with the new archivers for the computation of E. Finally, the behaviour of the archiver, as well as the efficiency of the resulting search procedure, will be demonstrated on some academic functions as well as on three models related to space mission design.
KW - approximate solutions
KW - differential evolution
KW - single objective optimization
KW - space mission design
UR - http://www.scopus.com/inward/record.url?scp=84990370544&partnerID=8YFLogxK
U2 - 10.1177/0954410011413693
DO - 10.1177/0954410011413693
M3 - Artículo
SN - 0954-4100
VL - 225
SP - 1229
EP - 1242
JO - Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering
JF - Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering
IS - 11
ER -