Complementing Solutions for Facility Location Optimization via Video Game Crowdsourcing and Machine Learning Approach

The facility location problem (FLP) is a complex optimization that has been widely researched and applied in industry. In this research, we proposed two innovative approaches to complement the limitations of traditional methods, such as heuristics, metaheuristics, genetic algorithms. first approach involves utilizing crowdsourcing through video game players obtain improved solutions, filling gap existing research on for FLP. second leverages machine learning techniques, specifically prediction provide an efficient exploration solution space. Our findings indicate techniques can solutions by providing more comprehensive solving FLP gaps Furthermore, predictive models are decision making quick insights into system’s behavior. conclusion, contributes advancement problem-solving potential implications wide range complex, NP-hard problems various domains.