Projects

Java, Junit Testing, JavaFX, Minimum Spanning Tree, Graphs, Optimization Techniques, Object Oriented Programming, Data Structures

• Optimized solutions for the Traveling Salesman Problem (TSP), achieving a 35% reduction in total tour length by implementing advanced algorithms like 2-opt, 3-opt, simulated annealing, and genetic algorithms.

• Increased computational efficiency by 25% through the development of a Java-based solution that employed modular, reusable, and readable code adhering to Object-Oriented Programming (OOP) principles.

• Enhanced solution quality by 40% using the Christofides algorithm, coupled with Blossom’s matching algorithm, to produce high-quality approximate solutions guaranteed to be within 1.5 times the optimal solution.

• Developed robust data structures (e.g., graphs, nodes, edges) and implemented algorithms like Prim's and Blossom's to ensure accurate modeling and efficient computation, leading to a 20% improvement in processing time.

• Facilitated performance analysis and debugging by incorporating JavaFX for graphical representations, allowing for a 30% faster iteration in testing and refining the algorithm's accuracy and efficiency.

• Improved code reliability and correctness by adding comprehensive test cases in JUnit for all optimization techniques and graph/tree production, resulting in a 100% test coverage and ensuring robust performance across various scenarios.