S. Vaithyanathan et al., MASSIVELY-PARALLEL ANALOG TABU SEARCH USING NEURAL NETWORKS APPLIED TO SIMPLE PLANT LOCATION-PROBLEMS, European journal of operational research, 93(2), 1996, pp. 317-330
Citations number
37
Categorie Soggetti
Management,"Operatione Research & Management Science","Operatione Research & Management Science
Neural networks and tabu search are two very significant techniques wh
ich have emerged recently for the solution of discrete optimization pr
oblems. Neural networks possess the desirable quality of implementabil
ity in massively parallel hardware while the tabu search metaheuristic
shows great promise as a powerful global search method. Tabu Neural N
etwork (TANN) integrates an analog version of the short term memory co
mponent of tabu search with neural networks to generate a massively pa
rallel, analog global search strategy that is hardware implementable.
In TANN, both the choice of the element to enter the tabu list as well
as the maintenance of the decision elements in tabu status is accompl
ished via neuronal activities. In this paper we apply TANN to the simp
le plant location problem. Comparisons with the Hopfield-Tank network
show an average improvement of about 85% in the quality of solutions o
btained.