Packing Optimization Method Based On Biogeography-based Optimization

The traditional manual loading and unloading storage process can no longer meet the increasing transportation needs,so the intelligent storage terminal system has received extensive attention.However,the cargo distribution and transportation process,as an important link in the intelligent warehousing terminal,still has the problems of low transportation efficiency,low utilization rate of loading space and long transportation time.Therefore,it is more important to further optimize and adjust the transportation structure,improve the comprehensive transportation efficiency,reduce the logistics cost,and optimize and adjust the transportation system.The optimization of transportation routes has become an important direction to solve the problem of transportation efficiency.In view of the current situation of low transportation efficiency,this paper studies from the following aspects:Design optimization models for transport processes with loading constraints.In this paper,the Biogeography-Based Optimization(BBO)and the two-dimensional rectangular loading algorithm are used to jointly optimize the cargo loading route and cargo loading rate to improve the packing problem(PP).and Vehicle Routing Problem(VRP).According to the demand of goods,the complex cargo loading problem is simplified into two-dimensional space for optimization.At the same time,the situation that the cargo can be rotated is considered to improve the utilization of the capacity in the vehicle.In addition,allowing the vehicle to return to the station multiple times,the two-dimensional bin packing problem is combined with the routing optimization problem to propose a transport path optimization problem with two-dimensional bin packing constraints(2DPP-VRP).According to the needs of optimization solution,this paper improves the deficiencies of BBO in application.On the one hand,in view of the slow convergence of the BBO algorithm and the easy loss of the optimal solution in the actual iterative process,a biogeographical optimization algorithm(Elite-based BBO,E-BBO)with an elite retention strategy is proposed.Implement further optimization of 2DPP-VRP.E-BBO adopts the elite retention strategy to save the optimal solution generated so far in the iterative process of the algorithm,and directly copy it to the next generation without migration and mutation operations.On the other hand,in order to solve the problem that the optimization process requires multiple calls to load judgment,which leads to a significant increase in time,a biogeographic optimization algorithm with ε constraints(ε-BBO)is proposed in this paper.The improved ε-BBO algorithm can relax the constraints and make it more efficient to generate the initial solution of BBO;through the evaluation method of the new fitness function,in the iterative process,the infeasible solution is gradually transformed into a feasible solution;The solution can also participate in the iteration,so that the new individuals generated can more easily generate good individuals when migrating and mutating.In order to verify the feasibility of the algorithm proposed in this paper,the traditional BBO algorithm is compared with the improved algorithm.It can be seen that the use of EBBO and ε-BBO has obvious advantages in optimizing speed and path length.To sum up,the improved BBO algorithm proposed in this paper has positive theoretical significance and application value for improving the routing optimization problem of two-dimensional loading.