Study on Automatic Stereoscopic Warehouse Slotting Optimization Based on Genetic Annealing Algorithm

Yang-Yang ZHU, Kong-Yu YANG

Abstract


For the automatic warehouse slotting optimization problems, the mathematical model of multi-objective optimization is established in order to improve the turnover efficiency and meet the requirements of shelf stability. Combined the local search ability of simulated annealing algorithm with the fast global searching ability of genetic algorithm, the genetic annealing algorithm based on slotting optimization is proposed and applied to the solution of the mathematical model. The shelf rated load weight is added to the constraint conditions, which ensures the operational reliability and stability of the automated warehouse. The algorithm is verified by simulation with MATLAB, which showed that genetic annealing algorithm can more effectively solve the problem of slotting optimization.

Keywords


Automated stereoscopic warehouse, Slotting optimization, Genetic annealing algorithm.


DOI
10.12783/dtssehs/icss2016/9172

Full Text:

PDF