This paper presents multi-criteria warehouses location problem in the logistics network. In order to solve this problem the location model was developed. The limitations and optimization criteria of the model were determined. Optimization criteria refer to transportation costs, costs associated with warehouses, e.g.: local taxes, expenditure on starting the warehouse, the constant costs, the labour force costs, the purchase costs of the additional land for the expansion, the transition costs of the raw material via the warehouses. The final location of warehouse facilities was obtained using a genetic algorithm. The genetic algorithm was developed in order to solve the multi-criteria warehouses location problem. This paper describes the stages of the genetic algorithm i.e. the stage of designating the initial population, the crossover and mutation process, the adaptation function. In this paper, the process of calibration of this algorithm was presented. The results of the genetic algorithm were compared with the random results.
A Genetic Algorithm for Multi-Period Location Problem with Modular Emergency Facilities and Backup Services
