| Project/Area Number |
20K04739
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Multi-year Fund |
|---|
| Section | 一般 |
|---|
| Review Section |
Basic Section 22050:Civil engineering plan and transportation engineering-related
|
|---|
| Research Institution | Kyoto University |
|---|
Principal Investigator |
|
|---|
| Project Period (FY) |
2020-04-01 – 2024-03-31
|
| Project Status |
Completed (Fiscal Year 2023)
|
| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2022: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2021: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2020: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
|
|---|
| Keywords | Multiple allocation / Hub location and Routing / Mathematical Modelling |
|---|
| Outline of Research at the Start |
Operations of a large urban freight carrier are modeled using Hub Location and Routing Problem (HRLP). Usually, depots (hubs) are located and each branch office/customer is assigned to a single hub forming a cluster. If a pickup and delivery demand is realized between customers assigned to two different hubs, a large detour and would generate extra costs and emissions. This problem can be managed by Multiple Allocation HLRP (MAHLRP). This research aims at mathematical modelling of the MAHLRP. An exact optimization algorithm as well as heuristics algorithm would be developed to solve it.
|
| Outline of Annual Research Achievements |
Operations of a large urban freight carrier are modelled using Hub Location and Routing Problem (HRLP). In this research, we developed exact and heuristics solutions for the Multi-Allocation Hub Location Routing Problem (MAHLRP). The heuristics version is based on the adaptive large neighborhood decomposition search (ALNDS). We also developed an application of the MAHLRP in solving warehouse matching platform system (WMPS).
In the final fiscal year, we continued to develop the exact solution algorithm for the MAHLRP based on branch and price scheme. The MAHLRP is decomposed in the master problem and a subproblem. The subproblem is solved at each hub to generate promising allocations and routing. As non-hub nodes can be assigned to many hubs simultaneously, it effects the capacity utilization of the multiple chosen hubs. Therefore, a novel approach has been used in the master problem where the capacity constraints are kept in it, which are normally moved to the subproblem. In order to accelerate the process, subproblem is solved at the already open hubs in the previous iteration; once this process fails to deliver promising new columns, unopen hubs are tried. Its performance and comparison with commercially available software (CPLEX) and problems (i.e. SAHLRP) has been done, It is found out that the proposed exact algorithm can solve larger problem than the CPLX in a much shorter time. As a future work, we are in process of extending our work to develop stochastic and time windows variants of the HLRP.
|
