HOPFIELD NEURAL NETWORK FOR A TRANSNATIONAL ENTERPRISE'S MANUFACTURING NETWORK

Multinational enterprises (MNEs) have to deal with two main issues. They need to define a suitable configuration for the activities of the chain value and to coordinate the so obtained network of facilities. The complexity of such issues and the impact of the managerial decisions on MNEs' performance are emphasized due to the international-wide economic scenario with which MNEs have to face. In this paper we focus on the coordination problems. In particular, we refer to transnational enterprises, i.e. MNEs which pursue a high coordination among their activities dispersed throughout the world.
We utilize an approach based on neural networks and, in particular, on a Hopfield neural network (HNN). We consider a simple model of the logistic network of a MNE, in order to describe the approach. The objective approach is the minimization of the total cost, that is the sum of production and transportation costs. The approach allows to handle non-linear cost functions and proves effective in determining the optimal solution.