In view of the problems of fresh food distribution, this paper analyzes the actual situation of fresh food distribution, selects total cost minimization and customer satisfaction maximization as optimization objectives, then adds time windows and other constraints to construct a dual-objective reefer truck path planning model, and uses genetic algorithm combined with greedy algorithm to solve. The experimental simulation results show that the algorithm of the article has good planning effect in path planning.
In response to the traditional Dijkstra algorithm, the long search time of pheromone and the occasional redundant inflection points When the final path is obtained can lead to the inefficiency of the algorithm due to its many traversed nodes. Therefore, this paper proposes the use of pheromone calculation method to improve Dijkstra's algorithm. The experimental results show that the optimized algorithm can largely reduce the inflection points generated during path planning and reduce the movement cost of the mobile robot path finding.
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