Description

The video below demonstrates the content of this downloadable virtual project.

This downloadable virtual product contains a barge transport SimPy model. The product comprises a Python framework and tutorial for simulating barge transports on a River. The product includes a case study for Mississippi River barge transport and an exemplary model implementation in Python consuming the framework and solving the case study. The framework is developed in Python using SimPy, a discrete-event simulation package for Python.

In short, this product includes:

• Framework in Python for modelling and simulating barge transports.
• Detailed case study description of barge transport between Cairo and New Orleans.
• Example model consuming the framework and solving the case study.
• Configuration file with relevant parameters related to the case study.

The framework uses SimPy. The framework tracks and visualizes relevant KPIs.

Who will benefit from this barge transport SimPy model?

This downloadable simulation product suits supply chain analysts, operations researchers, transport planners, and students that want to:

• Learn about discrete-event simulation in Python (SimPy).
• Learn about barge transport planning and operation.
• Learn how to model barge transport processes in Python (SimPy).
• Improve existing barge transport processes and projects.

Barge transport case study solved by this model

Barges are loaded in Cairo (IL, USA). In Cairo, laden barges wait for a boat to pick them up. A boat can pick up a large amount of barges and transports laden barges to New Orleans. In New Orleans, barges are unloaded and transported back to Cairo. Both loading and unloading operations are subject to minimum processing times and schedules. An additional constraint is that laden transport from Cairo to New Orleans moves at a different speed than unladen transport from New Orleans to Cairo.

Below image shows the relevant part of the Mississippi River on which the barge transport takes place.

For better understanding of barge transports also see below screenshot of a Google Maps satellite image of barges transported by a boat.

Relevant KPIs provided by barge transport SimPy model

The simulation framework contained by this product tracks relevant KPIs and outputs them visually.

The following KPIs supported by the framework:

• Position of each boat on the river over time
• Cumulative laden barges delivered for given barge count, per boat over time

Visual KPI examples, as outputted by the framework, are e.g. the ones shown below.

Learn more about simulation modeling in Python

You can find several contributions on SCDA related to discrete-event simulation and SimPy.

Here are some exemplary articles for you to read:

• Link: Poultry supply chain simulator with SimPy
• Link: Job shop simulation in Python in SimPy
• Link: Visualizing stats with salabim DES in Python
• Link: Poultry supply chain simpy library and model