A dimension-reduction algorithm for multi-stage decision problems with returns in a partially ordered set
RAIRO - Operations Research - Recherche Opérationnelle, Tome 36 (2002) no. 3, pp. 175-190.

In this paper a two-stage algorithm for finding non- dominated subsets of partially ordered sets is established. A connection is then made with dimension reduction in time-dependent dynamic programming via the notion of a bounding label, a function that bounds the state-transition cost functions. In this context, the computational burden is partitioned between a time-independent dynamic programming step carried out on the bounding label and a direct evaluation carried out on a subset of “real” valued decisions. A computational application to time-dependent fuzzy dynamic programming is presented.

DOI : 10.1051/ro:2003001
Mots-clés : multi-criteria optimization, time-variant networks, dimension reduction 
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     author = {Getachew, Teodros and Kostreva, Michael M.},
     title = {A dimension-reduction algorithm for multi-stage decision problems with returns in a partially ordered set},
     journal = {RAIRO - Operations Research - Recherche Op\'erationnelle},
     pages = {175--190},
     publisher = {EDP-Sciences},
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     doi = {10.1051/ro:2003001},
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Getachew, Teodros; Kostreva, Michael M. A dimension-reduction algorithm for multi-stage decision problems with returns in a partially ordered set. RAIRO - Operations Research - Recherche Opérationnelle, Tome 36 (2002) no. 3, pp. 175-190. doi : 10.1051/ro:2003001. http://archive.numdam.org/articles/10.1051/ro:2003001/

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