Picking Route Optimization of Automated Warehouse Based on Improved Genetic Algorithms

Abstract

In order to improve the efficiency of automated warehouse, the order-picking task of the fixed shelve was researched and analysed. The picking mathematical model of automated warehouse was established and attributed to the classical traveling salesman problem (TSP) model. At the same time, using an improved genetic algorithms(improved GAs) solved the optimization problem. Firstly, the initial population of the algorithm was optimized, and then a 'reverse evolution operator' was introduced in the improved genetic algorithms because of the lack of local optimization ability of genetic algorithm. Results of experiments verify that the method can acquire satisfying the demands of the route picking and optimization of speed.

Control System Design for Electric-Intensive Mobile Rack

“…Goetschalckx Marc and McGinnis Leon in 2004 present several models for the design of warehousing systems that use modular drawers and bin shelving, storage technologies [2]; Wang, P G, Qi X M, Zong X P, et al, researched and analyzed the order-picking task of the fixed rack to improve the efficiency of automated warehouse [3]; Guezzen, Amine Hakim, Sari Zaki, Ghomri Latefa in 2011 given a system which consists of storage racks moving laterally on rails so that one can open an aisle between any two joint racks, storage/retrieval (S/R) machines, the control system and an input/output (I/O) station; Sari Z, Hamzaoui A in 2013 aim to determine the optimal dimensions of a flow rack automated storage and retrieval system (AS/RS) using a single machine for storage and retrieval operations [4]. These optimal dimensions are evaluated for minimum expected travel times of the storage and retrieval machine.…”