The objective of this study is to develop a hybrid heuristic (HH) for
solving the generalized assignment problem (GAP) and conduct a computa
tional comparison with the leading alternative heuristic approaches. H
H is designed around the two best known heuristics: Heuristic GAP (HGA
P) and Variable-Depth-Search Heuristic (VDSH). Previous performance ch
aracteristic studies have shown that HGAP dominates VDSH in terms of s
olution CPU time, while VDSH obtains solutions of 13% to 300% better q
uality within a 'reasonable' time. The main idea in this paper is to h
ybridize the two approaches, such that the inherent values of both heu
ristics are realized.