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Overview

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The Supply Chain Simulator is a sample model provided and developed by Simudyne for the purpose of demonstrating how a modeller might use the Supply Chain Toolkit to develop a simulation of a supply chain.

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The following docs will be broken up into the below sections:

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  1. Introduction to Model Concepts
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  2. Model Components
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  3. Scenario & Strategy Analysis
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  4. Custom Dashboard
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Each section will reference the code available at the link below. Be aware that some environments might require installing Java and Python libraries to run the model, and the custom dashboard included in the package.

\n\n\tDownload Model Files\n\n

Introduction to Model Concepts

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The supply chain model is an example of a pull system built with the Supply Chain Toolkit released in version 2.6. The purpose of this model is to demonstrate how a supply chain network model that contains customers, warehouses, and production facilities.

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This sample model contains many of the necessary components, communication loops, and mechanisms that would be found in a larger production-like system.

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An agent-based framework of this type provides the user with the means to explore a wide range of problems and optimizations to a supply chain network, such as facility placement, alternative transport mechanisms, fulfillment strategy design, inventory placement, automation, etc.

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In this particular model, the structure is initialized by ingesting some dummy data that includes facility information, like the geographical locations and names of those facilities, and the topographical information that is used to define how the facilities are connected to one another (routes between the facilities).

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This defines the distribution network. To connect the distribution network to the end customer, we introduce a MarketPlace agent where customers can send orders based on their own internal spending preferences and warehouses can share the current state of their inventory. This market mechanism acts as a centralized place where different kinds of prioritization or optimization algorithms could be applied.

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To summarize, the communication loop during a step of the simulation begins with customers sending orders and warehouses sharing inventory, orders are matched at the marketplace, which feeds into fulfillment at the warehouse, and the passing on of demand information to the production facilities. Customer orders drive demand at the production facility, in this respect we can define the system as a \"pull\" system.

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Below is a screenshot from the Network view in the Simudyne Console:

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