russian doll search
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2018 ◽  
Vol 234 ◽  
pp. 131-138 ◽  
Author(s):  
Timo Gschwind ◽  
Stefan Irnich ◽  
Isabel Podlinski


2010 ◽  
Vol 5 (4) ◽  
pp. 631-638 ◽  
Author(s):  
Patric R. J. Östergård ◽  
Vesa P. Vaskelainen




2002 ◽  
Vol 11 (03) ◽  
pp. 425-436 ◽  
Author(s):  
MOHAMED TOUNSI ◽  
PHILIPPE DAVID

In this paper we introduce a new method based on Russian Doll Search (RDS) for solving optimization problems expressed as Valued Constraint Satisfaction Problems (VCSPs). The RDS method solves problems of size n (where n is the number of variables) by replacing one search by n successive searches on nested subproblems using the results of each search to produce a better lower bound. The main idea of our method is to introduce the variables through the successive searches not one by one but by sets of k variables. We present two variants of our method: the first one where the number k is fixed, noted kfRDS; the second one, kvRDS, where k can be variable. Finally, we show that our method improves RDS on daily management of an earth observation satellite.



Author(s):  
Pedro Mesegue ◽  
Martí Sánchez ◽  
Gérard Verfaillie
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