Optimizing Vehicle Routing for Perishable Products with Time Window Constraints:
A Case Study on Bread Distribution
Keywords:
Capacitated vehicle routing problem with time windows, Bread distribution, Simulated annealing, Adaptive large neighborhood search, Genetic algorithmAbstract
This research investigates the application of optimization methods to the Capacitated Vehicle Routing Problem with Time Windows in the context of bread distribution for the efficiency of different approach for managing large-scale goods delivery. Managing this distribution requires considering complexities such as travel distance, vehicle capacity, and time windows. Specifically, it compares the performance of ALNS, SA, and GA in minimizing total travel distance while adhering to strict delivery windows. The research is conducted across different cases, each distinguished by varying levels of demand, nodes, and time windows for each case. Based on four cases, ALNS is the most effective method among the three methods in optimizing bread distribution. It was averagely 33.02% more efficient than SA and 57.21% than GA for minimizing travel distance and offering a robust solution, improving delivery efficiency across different case scenarios.
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