Optimizing Operations: A Practical Guide to Operations Research Techniques with Python
Introduction:
Greetings, Medium community! I’m thrilled to introduce my latest book, “Optimizing Operations: A Practical Guide to Operations Research Techniques with Python.” This endeavor is born out of a deep passion for Operations Research, project management, and the untapped potential of Python in decision-making processes. What makes this guide unique is its commitment to using no external optimization packages like CPLEX or GUROBI. Instead, it empowers you to develop your own solutions, fostering a deeper understanding of the optimization process.
What’s Inside:
1. Practical Python Implementation:
Embark on a journey into Python coding tailored for Operations Research enthusiasts. Whether you’re new to coding or aiming to enhance your skills, each chapter is designed to empower you with the ability to implement what you learn immediately. The book deliberately avoids external optimization packages, encouraging hands-on coding for a more comprehensive learning experience.
2. Decision Analysis and Beyond:
Explore the intricacies of decision analysis, unravel the mysteries of queuing theory, and witness the real-world applications of optimization techniques — all achieved without relying on external packages. The book goes beyond theory, providing tangible examples and Python code to ensure that the concepts are not just understood but applied effectively.
3. Real-world Applications in Supply Chain and Network Optimization:
Discover how to apply optimization techniques to solve real-world challenges in supply chain management, network optimization, airline scheduling, and more — all without the aid of external packages. Each application is accompanied by practical insights and Python implementations, bridging the gap between theory and industry relevance.
The objective is to find the optimal values of that minimize the total transportation cost while satisfying the demand constraints and supply constraints.
Solution
This basic Python code solves a simplified supply chain optimization problem without using any external packages. The example demonstrates how products should be transported from suppliers to manufacturing plants to distribution centers to meet demand while minimizing transportation costs.
About the Author:
Allow me to introduce myself. I am Himanshu Bhardwaj, an experienced project and operations management professional with a decade of international experience. My journey includes an MBA from the Indian Institute of Management Shillong and an M. Sc. Tech from the Indian Institute of Technology, Dhanbad. With expertise in Analytics, Machine Learning, and Python coding, I bring a unique blend of skills to the table.
Get Your Copy:
Curious to delve into the world of Operations Research and Python coding without relying on external packages? “Optimizing Operations” is now available! You can [purchase it on Amazon https://amzn.eu/d/2GaGWvd . Join me on this transformative journey to optimize decision-making processes and embrace the power of Python in operational efficiency.
Conclusion:
Thank you for joining me on this exciting venture into the world of optimization. I invite you to explore “Optimizing Operations,” engage in the conversation, and experiment with the provided examples and code snippets. Feel free to share your thoughts, ask questions, and let’s collectively optimize the way we approach challenges in operations and decision-making.
Happy reading and coding!
Himanshu Bhardwaj
[LinkedIn Profile]
hemi.bhardwaj84@gmail.com
