Smart Farm Picking and Distribution Integration : Discrete Artificial Bee Colony Algorithm

摘要

With the development of agricultural intelligence, the efficiency of picking and transportation of agricultural products directly affects the income of agricultural products. This paper proposes an integrated scheduling problem of scheduling picking robots and planning distribution vehicle routing to improve the production efficiency of agricultural products. With the objective of minimizing total cost, an efficient discrete artificial bee colony algorithm (DABC) is designed. In the scheduling phase of picking robots, the picking tasks are assigned to agricultural robots, and then an optimal path is found for each agricultural robot to complete its assigned tasks. In the vehicle route planning phase, the delivery tasks are assigned to vehicles and sorted to find the optimal route. Based on the characteristics of the problem, an integer encoding method is first used, and a high-quality and diverse initial population is generated using the nearest neighbor heuristic algorithm. Neighbor-hood operators and diversified local search opera-tors are introduced to prevent the algorithm from getting stuck in local optima. Experimental results demonstrate that the improved discrete artificial bee colony algorithm performs better.