Exact and heuristic algorithms for the interval data robust assignment problem

Jordi Pereira, Igor Averbakh

Resultado de la investigación: Contribución a una revistaArtículorevisión exhaustiva

37 Citas (Scopus)

Resumen

We consider the Assignment Problem with interval data, where it is assumed that only upper and lower bounds are known for each cost coefficient. It is required to find a minmax regret assignment. The problem is known to be strongly NP-hard. We present and compare computationally several exact and heuristic methods, including Benders decomposition, using CPLEX, a variable depth neighborhood local search, and two hybrid population-based heuristics. We report results of extensive computational experiments.

Idioma originalInglés
Páginas (desde-hasta)1153-1163
Número de páginas11
PublicaciónComputers and Operations Research
Volumen38
N.º8
DOI
EstadoPublicada - ago. 2011
Publicado de forma externa

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