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Optimization Models for Business Applications: Project Collection

Overview

This repository contains a collection of small projects that demonstrate the application of various optimization techniques and operations research methods to solve real-world problems. Each project focuses on different aspects of business analytics, ranging from linear programming and mixed-integer programming to non-linear optimization. The projects span multiple domains, including transportation, job assignment, environmental management, and logistics.

Project Collection:

The full collection of small projects can be found in:

Project Highlights

Here are some examples of the types of projects included in this collection:

1. Transportation Problem - Car Redistribution for CaaS Ltd

  • Objective: Optimize the redistribution of electric cars across different areas in Helsinki to meet predicted demand while minimizing total driving time.
  • Key Techniques: Network Linear Programming (LP)
  • Outcome: Achieved optimal car transfers with a total driving time of 451 minutes.

2. Assignment Problem - Engineer Job Assignment for FIXITNOW

  • Objective: Minimize labor costs by optimally assigning engineers to jobs based on their skills and associated costs.
  • Key Techniques: Linear Programming (LP)
  • Outcome: Identified the optimal assignment of engineers, resulting in a total cost of 342 units.

3. Transshipment Model - Cartboard Distribution for Pulp & Paper Ltd

  • Objective: Minimize total transportation costs while satisfying customer demands and production capacities.
  • Key Techniques: Transshipment LP Model
  • Outcome: Optimized distribution network with a total transportation cost of 3,490,420 euros.

4. Project Portfolio Selection - Rewetting Actions in Järviniemi

  • Objective: Maximize biodiversity benefits and minimize greenhouse gas emissions by selecting the optimal combination of rewetting actions in the Järviniemi area.
  • Key Techniques: Binary Linear Programming (BLP)
  • Outcome: Selected an optimal portfolio of actions that reduced GHG emissions by 298,863 tons CO2 and increased biodiversity by 152 species.

5. Transportation Problem with Non-Linear Costs - P&T Company

  • Objective: Minimize transportation costs for the distribution of canned peas considering non-linear cost functions due to the impact of transportation volumes on costs.
  • Key Techniques: Non-Linear Programming (NLP)
  • Outcome: Optimized transportation costs to 188,177.11 $ with the current distribution plan.

Skills and Techniques

The projects in this collection demonstrate proficiency in a variety of optimization and operations research techniques, including:

  • Linear Programming (LP)
  • Mixed-Integer Linear Programming (MILP)
  • Non-Linear Programming (NLP)
  • Network Optimization
  • Binary Linear Programming (BLP)
  • Data Visualization

Conclusion

This collection showcases the practical application of operations research and optimization methods to solve complex problems across different operational domains. Each project is designed to provide insights into the process of modeling, solving, and interpreting the results of optimization problems in real-world scenarios.

Disclaimer

All data, company names, and scenarios used in these projects are entirely synthetic and have been created solely for educational and analytical purposes. Any resemblance to real companies or real-life data is purely coincidental. The companies mentioned in these projects may not exist in reality, and the data provided does not represent any real-world entities or situations.