Optimizing Logistics Distribution Routes: A Graph Theory Approach
By analyzing different route combinations, it becomes possible to identify the optimal route that minimizes the overall costs.
By analyzing different route combinations, it becomes possible to identify the optimal route that minimizes the overall costs.
Nowadays, product distribution is extremely complex. The decision makers face the challenge of considering multiple parameters to determine the optimum decision. A key consideration in decision making is minimizing distribution costs to achieve cost-effective delivery of goods or products to customers. The selection of distribution routes significantly affects these costs, making route optimization crucial for achieving cost efficiency.
Graph theory provides a powerful structure for representing the relationship between objects, including distribution routes that connect various locations. These routes can be connected based on factors such as distance, time, or total shipping costs between locations. By analyzing different route combinations, it becomes possible to identify the optimal route that minimizes the overall costs.
This 3-days online workshop is a beginner-friendly Deep Learning using Python. Students will learn how to apply graph theory in optimizing distribution routes using Python. This will help students gain insights into the practical benefits and potential applications of graph theory to the specific business processes in their respective industries. One Instructor and two Teaching Assistants will help participants troubleshoot or help with any difficulties encountered.
NOTE: This workshop will be delivered in Bahasa Indonesia.
Upon completion of this workshop, you will be able to:
Python Programming Basics
Fundamentals of Graph Theory
Case Study: Optimizing Logistics Distribution Routes
This testimonial video is taken after our previous Online Data Science Series: Time Series Analysis for Business Forecasting.
Our learning format is online-interactive, you will feel the interactive experience as if you were present in a physical classroom. You can access the class using your Zoom account on pre-defined dates.
Workshops in this series are tailored to casual programmers and non-programmers that are taking their first steps into data science. It assumes no prior knowledge or academic background, and attendees will be introduced to the beautiful art of writing R / Python code to produce data visualization and build machine learning models. The workshop has a gentle learning slope that is designed with non-technical professionals and academics in mind.
If I don’t have any IT or programming skills, can I still attend this workshop?
Yes, you can still attend the workshop as it is a beginner-friendly workshop.
How to join the interactive-online learning class after I’ve done the payment & registration?
Our system will send you an email containing a link and details to join a Google Classroom.
What platform will be utilized for this online-interactive learning workshop?
Online learning will be conducted via Zoom.us, Link to join the Zoom Class will be announced via Google Classroom.
How will the participants receive the learning materials?
Learning materials can be obtain via Google Classroom
Would I receive a certificate after participating in the Workshop?
Yes, you will receive a certificate of completion.
Irfan Chairur Rachman is a Data Science Instructor at Algoritma Data Science School, bringing a wealth of expertise in the fields of informatics and machine learning. With his remarkable skills and deep understanding of data science, Irfan has consistently delivered outstanding results in various projects and consultative mentoring for numerous organizations such as Bank Central Indonesia, Sinarmas, and ADIRA.