A Fuzzy-Evolutionary Approach to the Problem of Optimisation and Decision-Support in Supply Chain Networks

Abstract

This chapter deals with the problem of balancing and optimising the multi-echelon supply chain network of an Australian ASX Top 50 company which specialises in the area of manufacturing agricultural chemicals. It takes into account sourcing of raw material, the processing of material, and the distribution of the final product. The difficulty of meeting order demand and balancing the plants’ utilisation while adhering to capacity constraints is addressed as well as the distribution and transportation of the intermediate and final products. The aim of the presented system is to minimise the time it takes to generate a factory plan while providing better accuracy and visibility of the material flow within the supply chain. The generation of factory plans within a short period of time allows for what-if-scenario analysis and strategic planning which would not have been possible otherwise. We present two approaches that drive a simulation to determine the quality of the generated solutions: an event-based approach and a fuzzy rule-based approach. While both of them are able to generate valid plans, the rule-based approach substantially outperforms the event-based one with respect to convergence time and quality of the solution.