Collaborative supply chain planning using the artificial neural network approach

Abstract

The purpose of this paper is to show how the concepts of collaborative agents and artificial neural networks (ANNs) can work together to enable collaborative supply chain planning (SCP). An agent‐based supply chain network is decomposed into multiple ANNs in a way that the actual customer requirements and the agents' goals and constraints are matched in different stages. An error‐minimising algorithm which models the agents' collaboration mechanism is used to train three ANNs, namely the supply net, the production net and the delivery net, for pursuing complete order fulfilment across the supply chain. In the example problem, the collaborative SCP paradigm is applied to determine the supply plan of an alliance of small firms, which provides assemble‐to‐order goods with short delivery lead‐time to a regional market. The calculation results showed that the ANN approach achieved complete order fulfilment and significantly increased the resource utilisation of all supply chain agents.