Thesis (BS Applied Mathematics) -- University of the Philippines Mindanao, 2010

Uncapacitated Facility Location Problem (UFLP) is a type of facility location problem which deals with the location and opening of a predefined number of facilities as to accommodate the demand of all the clients. It is an optimization problem which aimed to minimize the total cost incurred in both the opening of the facilities and connecting of all clients to the facilities. Genetic algorithm (GA) is a population based algorithm which is a powerful tool for solving search and optimization problems and deals with non-polynomial (NP) nature problems like UFLP, GA-UFLP was conducted to obtain the minimum total cost of UFLP using the genetic algorithm. The method was applied to both the small-scaled and large-scaled data set which is proportional to the former one. Unlike the small-scaled data set which was got from a journal, the large-scaled data set was randomly generated using the uniform probability distribution. Results showed the best solutions for the two data sets. It was observed that the best feasible solution obtained from the small-scaled GA-UFLP was the same to the optimal solution compared from the exact algorithm integer programming applied to UFLP (IP-UFLP). The large-scaled GA-UFLP was also able to produce the best solution because the results were the same for all the 30 trial runs conducted. Both data sets did not only produce the optimal solution but also the 50 best solutions using GA-UFLP. However, the additional studies especially on parameter setting was recommended for sensitivity analysis.