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Variable neighborhood search
NP-hardness of Euclidean sum-of-squares clustering
A recent proof of NP-hardness of Euclidean sum-of-squares clustering, due to Drineas et al. (Mach. Learn. 56:9–33, 2004), is not valid. An alternate short proof is provided.
Bicriterion Path Problems
Algorithms are provided for some of the bicriterion path problems in directed graphs, including polynomial algorithms for the MAXMIN-MAXMIN problem and the MINSUM-MAX MIN problem, and a pseudo-polynomial exact algorithm as well as a fullyPolynomial approximation scheme for the MINsUM-MINSUM problem.
Variable neighbourhood search: methods and applications
Variable neighbourhood search (VNS) is a metaheuristic, or a framework for building heuristics, based upon systematic changes of neighbourhoods both in descent phase, to find a local minimum, and in
Variable Neighbourhood Search
The basic idea of VNS is the change of neighbourhoods in the search for a better solution. VNS proceeds by a descent method to a local minimum exploring then, systematically or at random,
Roof duality, complementation and persistency in quadratic 0–1 optimization
The main result is that the four gaps associated with the four relaxations are equal, and a class of gap-free functions (properly including the supermodular ones) is exhibited.
An Introduction to Variable Neighborhood Search
A relatively unexplored approach to the design of heuristics, the guided change of neighborhood in the search process, is examined, which leads to a new metaheuristic, which is widely applicable.