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[کتاب][B] Optimization by GRASP
MGC Resende, CC Ribeiro - 2016 - Springer
Greedy randomized adaptive search procedures, or GRASP, were introduced by T. Feo and
M. Resende in 1989 as a probabilistic heuristic for solving hard set covering problems. Soon …
M. Resende in 1989 as a probabilistic heuristic for solving hard set covering problems. Soon …
Greedy randomized adaptive search procedures: advances and extensions
A greedy randomized adaptive search procedure (GRASP) is a multi-start metaheuristic for
combinatorial optimization problems, in which each iteration consists basically of two …
combinatorial optimization problems, in which each iteration consists basically of two …
An evolutionary approach for the p-next center problem
The p-next center problem is an extension of the classical p-center problem, in which a
backup center must be assigned to welcome users from a suddenly unavailable center …
backup center must be assigned to welcome users from a suddenly unavailable center …
Hybridizations of GRASP with path-relinking
A greedy randomized adaptive search procedure (GRASP) is a metaheuristic for
combinatorial optimization. GRASP heuristics are multistart procedures which apply local …
combinatorial optimization. GRASP heuristics are multistart procedures which apply local …
A hybrid of max–min ant system and linear programming for the k-covering problem
This paper presents a hybrid algorithm of linear programming (LP), max–min ant system,
and local search for solving large instances of the k-covering problem (SC k P). This …
and local search for solving large instances of the k-covering problem (SC k P). This …
MLQCC: an improved local search algorithm for the set k‐covering problem
The set k‐covering problem (SKCP) is NP‐hard and has important real‐world applications.
In this paper, we propose several improvements over typical algorithms for its solution. First …
In this paper, we propose several improvements over typical algorithms for its solution. First …
A heuristic algorithm for the set k-cover problem
The set k-cover problem (SkCP) is an extension of the classical set cover problem (SCP), in
which each row needs to be covered by at least k columns while the coverage cost is …
which each row needs to be covered by at least k columns while the coverage cost is …
[PDF][PDF] Combinatorial optimization methods for the (α, β)(α, β)-k Feature Set Problem
A Salehipour - 2019 - nova.newcastle.edu.au
This chapter brings a short introduction into the presented research thesis, as well as a brief
discussion regarding the role of optimization and operations research into computational …
discussion regarding the role of optimization and operations research into computational …
Ants for Identifying and Optimizing the Core Set K-Covering Problem
For large set k-covering problems, finding the set of core columns (CC), which includes
columns for which it is hard to decide their status in the optimal solution, and searching CC …
columns for which it is hard to decide their status in the optimal solution, and searching CC …
[PDF][PDF] Efficient methods of feature selection based on combinatorial optimization motivated by the analysis of large biological datasets
MR de Paula - 2012 - nova.newcastle.edu.au
According to Luscombe et al.(2001),“Bioinformatics is conceptualizing biology in terms of
macromolecules (in the sense of physical-chemistry) and then applying 'informatics' …
macromolecules (in the sense of physical-chemistry) and then applying 'informatics' …