Optimization Methods in Management Science
This course focuses on the decision-making process of analyzing, defining, representing and solving a numerous business problems and cases, employing a number of optimization methods and tools. The optimization methods introduced are applied to solve a broad number of real-world case studies from different domains and industries such as transportation and logistics, telecommunications, manufacturing and service operations, health care management, tourist management, maritime and shipping.
On completion of this course, students should be able to:
• understand the computational characteristics of different types of business problems
• design effective optimization methods for solving both complex and realistic size management science applications
Course contents
The course material includes the following thematic areas:
• Computational complexity and management science applications
• Large scale optimization and applications
• Approximation algorithms and applications
• Construction algorithms and applications
• Local search and neighborhood structures
• Iterative improvement algorithms
• Greedy Randomized Adaptive Search Procedures and applications
• Variable Neighborhood Search and Large Neighborhood Search
• Simulated Annealing and applications