List: Transportation Operations | Curated by Samir Saci | Medium

Sep 17, 2022

7 stories

1 save

Transportation Operations

In

TDS Archive

by

Samir Saci

Road Transportation Network Visualization with Python

Build Visualizations of your FTL Network Performance: deliveries/route, cost per ton and trucks size

Sep 9, 2020

A geographic map displaying a road transportation network in China with nodes connected by lines representing Full Truck Load (FTL) routes. The visualization includes route paths with metrics like delivery count, cost per ton, and truck size generated with Python. The map helps assess performance across different routes and locations. This visualization is useful for optimizing transportation efficiency and cost.

Sep 9, 2020

In

TDS Archive

by

Samir Saci

Build a Shipment Tracking Tool using a Telegram Bot

Design a Telegram Bot with Python that interacts with truck drivers, tracks your shipments and provides real-time visibility.

Mar 9, 2021

Mar 9, 2021

Samir Saci

Build a GPS Routing API with Python Flask

Create a free Distance Matrix API using Python Flask with a Selenium bot deployed on the cloud

Mar 14, 2021

Build a GPS Routing API with Python Flask

Mar 14, 2021

In

TDS Archive

by

Samir Saci

Containers Loading Optimization with Python

How can we use heuristic algorithms to find the right strategy to load a maximum number of pallets in a sea container?

Apr 23, 2021

A 3D rendering of two large shipping containers, one red and one green, with pallets stacked nearby. A red forklift is seen carrying a pallet toward one of the containers. This image visualizes the container loading process, with different pallet arrangements intended to maximize space utilization inside the sea containers. The scene demonstrates the need for optimization strategies to load a maximum number of pallets efficiently.Containers Loading Optimization with Python

Apr 23, 2021

In

TDS Archive

by

Samir Saci

Optimize E-Commerce Last-Mile Delivery with Python

Organize your routes to deliver parcels with a minimum number of drivers using optimization models with python

May 7, 2021

A diagram illustrating the last-mile delivery process for e-commerce optimization using Python. A truck is shown delivering parcels to a warehouse, from which a delivery person on a scooter distributes packages to multiple locations. Dotted lines connect the scooter to several drop-off points marked with question marks, representing unknown delivery destinations. The graphic emphasizes the process of organizing delivery routes to minimize the number of drivers needed for parcel delivery.

May 7, 2021

Samir Saci

Lean Six Sigma with Python — Chi-Squared Test

Perform a Chi-Squared Test to explain a shortage of drivers impacting your transportation network

Oct 30, 2021

Diagram illustrating the driver allocation problem in a transportation network. A factory sends goods to two warehouses — North and South — via an ERP system. Both warehouses are served by a transport company, which allocates drivers (D1, D2, D3). Black arrows represent balanced driver allocations to the North Warehouse, while red arrows indicate an unbalanced allocation to the South Warehouse, causing delays. This introduce Lean Six Sigma with Python using Chi-Squared Test.

Oct 30, 2021

In

TDS Archive

by

Samir Saci

Transportation Network Analysis with Graph Theory

Use graph theory with Python to optimize the road transportation network of a retail comp

Jan 12, 2022

A network visualization shows stores and delivery trucks as interconnected nodes. Stores are represented in different colors, likely indicating different regions. Each store connects to another based on previous deliveries. The network highlights which stores are frequently delivered together, with each line representing a delivery route. This graph can help optimize delivery routes by clustering stores together to increase efficiency.

Jan 12, 2022