Research On Optimizing Multi-person Collaborative Picking Path Based On Improved Fishbone Storage Layout

In order to improve market competitiveness,warehousing companies mainly study the efficiency of warehouse operations,picking operations account for 60% of the total warehouse operations,and improving the efficiency of picking operations can reduce warehouse operating costs.Therefore,the research of picking path in warehouse is a hot topic of current research.In this paper,the improved fishbone warehouse layout is taken as the research object.The picking path problem can be divided into a single vehicle for one order and multiple vehicles for one order depending on whether or not the load capacity of the picking equipment is considered.The picking path mathematical model of a single vehicle for one order takes the minimum distance a vehicle consumed leave from pickup & deposit point(P&D point)to pick all items and go back to the P&D point as the optimization target.Genetic algorithm(GA)and ant colony algorithm(ACO)are used to solve the model.In simulation experiments,the results of S-shaped,ACO and GA are analyzed and it shows that GA and ACO are better than S-shaped in solving the picking path problem.The optimization performance for GA is the same as for ACO.For multiple vehicles for one order,the total traveling distance for multiple vehicles to fulfil the customer's order is taken as the optimization goal.The experimental simulation shows that the GA and the ACO are feasible in solving picking optimization problem for multiple vehicles for one order.The larger the order,the better the ant colony algorithm solves the problem,Finally,the improved fishbone storage layout and multi-person collaborative optimization picking path were obtained.It's help to optimize the efficiency of picking operation in the improved fishbone warehouse.