| dc.description.abstract | This paper proposes a genetic algorithm approach to the vehicle routing problem with time
windows (VRPTW). The VRPTW is a well-known combinatorial optimization problem in which
a fleet of vehicles must serve a set of customers within predefined time windows while
minimizing the total travel distance. The problem is applied into a case study of Gemadept
company where the staff plans the routes manually and suffer much lost due to inaccuracy. The
raw data was processed by Python to replace the manual arrangement of the staff, then the model
was solved by CPLEX to find the optimum solution for the vehicle routine, and the results are
analyzed through sensitivity analysis. The proposed approach is expected to have important
practical applications in the transporting process of the company, where efficient routing and
scheduling of vehicles can lead to significant cost savings and improved service quality | en_US |
