Abstract for: Limits to Growth (of a Model) featuring Failure Analysis and Modeling Environment (FAME)

Networks are often modeled in discrete-event simulations to represent the physical behavior of routers, switches, packets, etc. A supply chain could similarly be modeled as a system of nodes and edges from origin to destination. When the desire is to model aggregate products (whether discrete packages or continuous flows) to examine the resilience of a network to disruptions, a system dynamics approach is adequate. This paper represents on-going work in modeling information flows through a network of nodes. It was meant to be a first principles look at simultaneously solving the minimum cost and maximum flow problems in the face of outages for a real application. We have shown how to use Sensitivity runs to analyze the trade space by combining node outages and measuring the resulting performance (deliveries) vs. cost (delays/lost products). We have also shown how to use Optimization runs to find a minimum cost or maximum flow path in the face of outages both in terms of probability and frequency. The resilience part of this paper is in how to manage capacity, “heal” the network, and where to put buffers in order to safeguard the network from unexpected outages. We often hear that the path is more important than the destination and this model encapsulates that saying by showing that there can be many paths for many products from many origins to many destinations…forward and backward.