An Improved Genetic Algorithm for the Uncapacitated Facility Location Problem and Applications in Oil and Gas Fields

Abstract

Abstract Uncapacitated Facility Location Problem (UFLP) is a NP-hard Problem that to determine the optimal Location of facilities. In this paper, the general Genetic Algorithm (gGA) is first introduced and adopted to solve a small case of UFLP (case1). Then an improved genetic algorithm (iGA) based on real coding is proposed to solve the UFLP problem. This paper mainly makes appropriate adjustments in the selection of fitness function, crossover operator and mutation operator to be more suitable for UFLP. Facilities thus can be roughly allocated according to the cost of facilities and the demands of customers. Case2 was calculated by several CAP data (CAP101, CAP103, CAP104, CAP131, CAP133, CAPB and CAPC) in OR-LIBRORY. The results proved that the iGA is feasible and effective, and it is found that 80% of the results obtained by the iGA are within 0.05% of the optimal solutions. Compared with several other common algorithms, the advantages of iGA increase as the scale of calculation increases. Finally, applying iGA to an on-site oilfield pipeline network, it was found that it can find the optimal solution in a short time.