Serious Gaming Learning: Supply Chain Multi-Agent Web-based Simulation Game

High levels of complexity and uncertainty, and various sources of risks, create challenges for supply chain networks in achieving satisfactory performance, but advances in Information Technology can help supply chain decision makers predict the magnitude and impact of the risks related to their decisions. The framework proposed in this paper offers a solution that integrates intelligent-agents, simulation modelling, and optimisation. Its friendly, animated, interactive web-based interface is especially designed to engage the user in a ‘serious game’ environment. Each user plays a specific role in the supply chain network, and encounters the consequences of their decisions. The optimisation engine embedded in the framework advises users about the optimum decisions and their anticipated performance outcomes. Genetics Algorithm (GA) and Case-Based Reasoning (CBR) are used to enhance the decision quality. A high-level communication protocol has been designed, developed and implemented to facilitate client/server communications, and allow intelligent-agents to inter-communicate easily and efficiently. The tool we develop offers equal value in supporting management decision-making, or in educating trainees in the realities of supply chain management.