Approximating the Pareto-front of a planar bi-objective competitive facility location and design problem ?
A new multi-objective evolutionary algorithm, called FEMOEA, is presented. Its aim is to obtain a discrete approximation of the Pareto-front of multi-objective optimization problems. It combines ideas from different multi-objective and single-objective optimization evolutionary algorithms. It also incorporates a new improving method and a new stopping rule. It has been applied to a hard-to-solve bi-objective continuous competitive facility location and design problem. Computational studies show that the new method outperforms, on average, both SPEA2 and NSGA-II.
pareto-front competitive location franchise system nonlinear bi-objective optimization problem evolutionary computation