2024-12-26
Seminar: Facility Location Optimization with Unsupervised Learning
Introduction:
The Department of Industrial Engineering of Kyrgyz-Turkish Manas University hosted an engaging seminar on 25.12.2024 titled "Using Unsupervised Learning in Some Optimization Problems," presented by Dr. Selçuk Gören. The seminar explored the potential of unsupervised learning algorithms, a subfield of artificial intelligence, to offer innovative solutions to complex optimization problems. In particular, the applications of clustering algorithms in facility location planning were examined in detail.
Seminar Content:
The seminar explained the basic principles of unsupervised learning and its role in optimization problems. Dr. Selçuk Gören explained how unsupervised learning methods, especially clustering algorithms such as K-means can be used in the processes of optimally positioning and arranging facilities such as factories, warehouses, or logistics centers. These algorithms analyze data by separating points with similar characteristics into clusters, thus helping to find optimal solutions that will increase efficiency in facility layout.
Importance of Facility Location Optimization:
An effective facility location is critical to reduce production costs, improve logistics processes, optimize workflow, and increase overall efficiency. Unsupervised learning algorithms analyze large and complex data sets that are difficult to solve with traditional methods, offering faster and more effective solutions. This provides businesses with a competitive advantage.
Contributions of the Seminar:
The seminar provided valuable information on the practical applications of unsupervised learning for industrial engineering students and academics. Participants had the opportunity to better understand the potential of artificial intelligence technologies in industrial processes. It was also emphasized that such seminars are an important source of motivation for students to develop innovative solutions in their future careers.
