Tabu Search for the Multilevel Generalized Assignment Problem
M. Laguna, J. P. Kelly, J. L. Gonzalez Velarde and F. Glover
European Journal of Operational Research, vol. 82, pp. 176-189 (1995)

Abstract
The multilevel generalized assignment problem (MGAP) differs from the
classical GAP in that agents can perform tasks at more than one efficiency
level. Important manufacturing problems, such as lot sizing, can be
formulated as MGAPs; however, the large number of variables in the
related 0-1 integer program makes the use of commercial optimization packages
impractical. In this paper, we present a heuristic approach to the solution
of the MGAP, which consists of a novel application of tabu search (TS). Our
TS method employs neighborhoods defined by ejection chains, that produce
moves of greater power without significantly increasing the computational
effort.
