Plants inspired algorithms for uncapacitated facility location problems

The Artificial Tree (AT) algorithm and Flower Pollination (FP) algorithm are algorithms inspired by life cycle of plants. AT algorithm is transformed by the growth law of trees while the FP algorithm is related with flower proliferation role in plants. This paper proposes these algorithms to solve the Uncapacitated Facility Location Problem (UFLP). Minimizing the sum of the fixed setup costs and customers serving costs is the objective of UFLP. Based on the computational result in given UFLP small number of data, both algorithms gave excellent result finding the minimum total costs. On the other hand, the AT algorithm performed better in bigger size of data than the FP algorithms. Moreover, higher number of population and iteration provided better computational performance in both algorithms. Higher number of switch probability of FP algorithm and constant maximum search number could help the algorithms to find better solution in solving the UFLP.