A (hybrid) GA Method building for the Location-allocation problems
At allocation level, the ALA method can be adopted to solve the (general) assignment in order to obtain the solution quickly
At location level, the evolutionary method by GA is applied to search whole location area
Chromosomes - a representation of starting solutions randomly generated
Initialisation - The initial locations of centres are randomly picked up from a rectangular region
Evaluation - Fitness value of the chromosomes is the sum of travel cost minimised from each centre to the demands assigned to and then, the ALA can be used to solve the allocation problem
Crossover, Mutation, and selection of the best individual