| Summary: | 碩士 === 國立交通大學 === 工業工程與管理學系 === 100 === The vehicle routing problem with time windows (VRPTW) has received much attention, and has been applied to solving many scheduling applications in transportation and logistics. The VRPTW considers a fleet of vehicles with specific capacity to serve a number of customers with various demands and time window constraints, with objective of finding the minimal number of vehicles and the shortest routing distance. However, the previous works for VRPTW did not consider drivers’ off-hour regulation. In practice, the purpose of drivers’ off-hour regulation is to improve the transportation safety by deducing the occurrence of fatigue and other pressure-related conditions on drivers. These rules can be transformed into the regulations on works hours and resting periods, and hence, the resulting drivers’ off-hour regulation has a major impact on the total traveling time. This paper presents a genetic algorithm for solving the vehicle routing problem with customers’ time windows and drivers’ off-hour regulation. The objective is to minimize the total traveling cost and the cost of the used number of vehicles. In this paper, four test problems with different scales are developed: 25 customers, 50 customers, 100 customers, and 150 customers, respectively. In the four test problems, only the optimal solution of the problem with 25 customers can be obtain by the brute-force method. Simulation results indicate that, after applying genetic algorithms to the test problem of 25 customers, the difference between the optimal solution and the average solution of 100 runs is less than 0.05%. As for the other test problems, we can find the appropriate parameter settings for genetic algorithms.
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