Algorithm, Computation, & Optimization Laboratory, the center of excellence in the development of optimization theory, algorithm design, and computational platforms.
To become a center of excellence in the development of optimization theory, algorithm design, computational platforms, and real-world applications
01.
To uphold the good reputation of the ACO lab, and serve as a liaison between lecturers & researchers and UI Industrial Engineering students.
02.
To foster a culture of collaboration among laboratory assistants.
03.
To develop the competencies of laboratory assistants, both academically and non-academically.
04.
To support student and lecturer research through the provision of adequate facilities and assistance.
Converting real world problem to mathematical model to orde to find the best alternative/decision while dealing with constraints. This applies to various scope, such as planning, transportation systems, and scheduling.
This covers topics such as:
Fokus pada pengembangan algoritma yang efisien dan skalabel untuk menyelesaikan permasalahan optimasi berskala besar dan berkompleksitas tinggi, khususnya permasalahan NP-hard. Topik penelitian meliputi:
* Metaheuristics
* Genetic Algorithms
* Evolutionary Algorithms
* Ant Colony Optimization
* Simulated Annealing
* Tabu Search
* Variable & Large Neighborhood Search
* Hybrid Metaheuristics
* Approximation Algorithms
* Parallel and Distributed Algorithms
Integrasi antara kecerdasan buatan dengan optimasi matematis untuk membangun sistem pengambilan keputusan yang adaptif, prediktif, dan otonom. Fokus penelitian meliputi:
* Machine Learning for Optimization
* Reinforcement Learning
* Deep Reinforcement Learning
* Hybrid AI–OR Methods
* Neural Combinatorial Optimization
* Data-driven Optimization
* Predictive and Prescriptive Analytics
* Digital Twins
* Intelligent Decision Support Systems
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