Practical Projects in Linear Programming, Integer Programming, Metaheuristics, and Decision Analytics with Java
Welcome to Operations Research and Optimization Projects with Java!
This course is designed for students, engineers, and professionals who want to master the fundamentals and applications of optimization techniques through real-world projects implemented in Java. While we use Java to model and solve problems, the focus is on optimization methods and decision science—not on teaching the Java language itself. A working knowledge of Java is recommended.
What you’ll learn
- Formulate and solve real-world optimization problems using Linear and Integer Programming in Java..
- Apply metaheuristic techniques such as Genetic Algorithms and Simulated Annealing to complex decision problems..
- Design and implement solutions for logistics and supply chain challenges like the Vehicle Routing Problem (VRP)..
- Use sequential decision-making methods and dynamic programming for adaptive planning and optimization..
Course Content
- Introduction –> 1 lecture • 3min.
- Linear Programming –> 1 lecture • 9min.
- Production Planning –> 1 lecture • 7min.
- Integer Programming –> 1 lecture • 4min.
- Vehicle Routing Problem –> 1 lecture • 11min.
- Genetic Algorithms –> 1 lecture • 8min.
- Simulated Annealing –> 1 lecture • 11min.
- Goal Programming –> 1 lecture • 8min.
- Sequential Decision Making –> 1 lecture • 16min.
Requirements
Welcome to Operations Research and Optimization Projects with Java!
This course is designed for students, engineers, and professionals who want to master the fundamentals and applications of optimization techniques through real-world projects implemented in Java. While we use Java to model and solve problems, the focus is on optimization methods and decision science—not on teaching the Java language itself. A working knowledge of Java is recommended.
Throughout this course, you will explore a wide spectrum of Operations Research (OR) and Optimization topics, including:
- Linear Programming (LP) and Integer Programming (IP): Learn how to formulate mathematical models for production planning, resource allocation, and scheduling problems, and implement them in Java.
- Metaheuristic Algorithms: Apply Genetic Algorithms and Simulated Annealing to solve complex optimization problems where exact methods struggle.
- Vehicle Routing Problem (VRP): Discover how to design and implement routing strategies for logistics and transportation systems.
- Sequential Decision Making (SDM): Understand how dynamic programming and Markov decision processes can be applied to adaptive planning and decision analytics.
- Production Planning and Simulation: Tackle industrial-scale problems involving capacity, scheduling, and efficiency trade-offs.
By the end of this course, you will be able to:
- Translate real-world optimization problems into mathematical models.
- Implement exact and heuristic algorithms in Java to solve these models.
- Compare solution methods, evaluate trade-offs, and understand when to apply each approach.
- Gain practical experience through project-based learning that bridges theory with application.
This course is ideal for those in industrial engineering, computer science, operations management, or data analytics who want to deepen their understanding of optimization and its implementation in Java. Whether you’re aiming to advance your academic knowledge or apply optimization to business and engineering challenges, this course will provide you with the tools and confidence to tackle complex decision-making problems.
Join now and start building a strong foundation in Operations Research and Optimization with Java through hands-on, project-driven learning!