Model presentation to emptying the picking warehouse with heterogeneous containers in emergency situations with swarm intelligence algorithms

Planning to empty warehouse cells is one of the most challenging issues in times of crisis. The need for emergency logistics for the efficient use of equipment is of great importance. In this study, a dual-objective planning model of routing and simultaneous scheduling of heterogeneous vehicles (picking containers)It has been suggested to evacuate the courier warehouse cells in emergency situations (non-compliance of the piece with the courier schedule) in order to minimize the movement time and maximize the reliability of the routes due to the congestion of the warehouse corridors. The developed Epsilon constraint method has been used to solve the proposed model. In the proposed model, the possibility of providing service for each warehouse cell that should be emptied by heterogeneous peak containers to logistics /warehouse areas with limited capacity is considered.To demonstrates the performance of the proposed model, the model is run on a random example and the computational results are presented. The results of problem-solving indicate a conflict between the objective functions used. In order to investigate the large-scale model, due to the Np-hard routing issues, three Particle Swarm Algorithms (PSO), Ant Colony (ACO), and Bee Colony (ABC), swarm intelligence algorithms were used and the results were compared with each other. The results of large-scale problem solving to find the best displacement path show better performance of the particle swarm algorithm.