Optimization decision model for truck terminal policy | |
| Author | Rittee Hongsakorn |
| Call Number | AIT Diss no.TE-03-02 |
| Subject(s) | Truck terminals--Mathematical models Truck terminals--Government policy Decision making--Mathematical models |
| Note | A dissertation submitted in partial fulfillment of the requirement for the degree of Doctor of Engineering, School of Civil Engineering |
| Publisher | Asian Institute of Technology |
| Series Statement | Dissertation ; no. TE-03-02 |
| Abstract | This dissertation presents a planar location optimization model, the significance of the truck trip conversion model and the speed-density interaction on the optimized truck terminal policy, and the sensitivity analysis. The model, which is developed based on the zonal aggregation concept, supports the decision on the truck terminal policy at a time cross section. The objective of the model is to minimize the costs due to the city logistics and the passenger travel activities. The decision variables of the model are the total number, the locations, and the capacities of the truck terminals. The truck trip conversion model and the zonal speeddensity interaction are introduced and equipped into the model to promote the interaction among the freight demand, traffic condition, logistics pattern, and the optimum policy. The truck trip conversion model converts the freight transportation demands into a set of truck trips that yields minimum transportation cost. The best combination of the truck size option and the terminal option is selected among all the feasible combinations for every freight demand origin-destination. For the truck size selection, two approaches are introduced. Firstly, the small truck approach tries to assign the goods to the small truck if possible. The lot, of which the weight does not exceed the small truck capacity, is assigned to the small trucks. Otherwise, they will be assigned to the large trucks. Secondly, the large truck approach tries to assign the goods to the large trucks if appropriate. Since the transportation cost of one large truck is less than that of two small trucks, the goods are assigned to the large trucks until it meets two conditions, i.e. i) the total weight of the rest of the small lot goods does not exceed the small truck capacity, and ii) the average weight of the small lot goods times the maximum number of trips per tour does not exceed the small truck capacity. An illustration is applied to the Tokyo Kubu area with the 1999 Japan Road Traffic Census (JRTC) data. The significant logistics parameters are retrieved from over 500,000 logistics tours. The 95 percentile of small and large truck capacities are 1,070 and 10,100 kilograms, respectively. Meanwhile, the 95 percentile maximum number of trips per tour is found out to be 11 trips per tour. The existing empty return rate is 42.4 percent. Then, all the decision variables are solved by the genetic algorithm (GA). The result indicates that the optimal number of truck terminals is five terminals, which can save . the total transportation cost by 7.39 billion yens per week comparing with that of the direct logistics system. The significance of the truck trip conversion model and the zonal speed-density interaction on the result are then investigated by three approaches. Firstly, freight demand approach resolves the best sites based on the weight-distance of the freight demand. Secondly, the converted truck trip approach calculates the optimal truck trips needed to handle the freight demand. Then, the locations are optimized based on the travel cost and the transfer costs of the logistics activities. Thirdly, the speed-density interaction approach, which is proposed in the disse11ation, integrates the influence of the trucks on the traffic condition. It is found that the speed-density interaction approach surpasses the others to support the truck terminal policy planning. In addition, the truck trip conversion shall not improve the reliability of the optimal locations without the zonal speed-density interaction. The sensitivity of the optimal truck terminal policy to the empty return rate (ER), the unit handling cost, and the city logistics pattern is analyzed and discussed. The disse11ation concludes that the optimal number of truck terminals is sensitive to the ER and the city logistics pattern but is insensitive to the unit handling cost. The optimal locations are sensitive to the city logistics pattern but are insensitive to the ER and the unit handling cost. The total truck terminal usage is sensitive to the ER, the unit handling cost, and the city logistics pattern. |
| Year | 2003 |
| Corresponding Series Added Entry | Asian Institute of Technology. Dissertation ; no. TE-03-02 |
| Type | Dissertation |
| School | School of Civil Engineering |
| Department | Department of Civil and Infrastucture Engineering (DCIE) |
| Academic Program/FoS | Transportation Engineering (TE) |
| Chairperson(s) | Hanaoka, Shinya;Sano, Kazushi; |
| Examination Committee(s) | Yordphol Tanaboriboon; Pannapa Herabat; Tripathi, Nitin Kumar;Kohler, Uwe ; |
| Scholarship Donor(s) | Siam University; |
| Degree | Thesis (Ph.D.) - Asian Institute of Technology, 2003 |