Transportation service procurement problem with transit time |
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| Institution: | 1. International Center of Management Science and Engineering, School of Management and Engineering, Nanjing University, Nanjing 210093, China;2. Department of Management Sciences, City University of Hong Kong, Tat Chee Avenue, Kowloon Tong, Hong Kong;1. Mathematical Sciences, Lund University, Box 118 Lund SE-22100, Sweden;2. Department of Mathematics and Statistics, University of Massachusetts, Amherst, MA 01003, United States;1. School of Information Technology, Jiangxi University of Finance and Economics, Nanchang 330013, Jiangxi, People’s Republic of China;2. Department of Management Sciences, City University of Hong Kong, Tat Chee Ave, Kowloon Tong, Hong Kong;3. Department of Computer Science, Xiamen University, Xiamen 361005, China;4. School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore 637371, Singapore;5. International Center of Management Science and Engineering, School of Management and Engineering, Nanjing University, Nanjing 210093, People’s Republic of China;1. School of Information Technology, Jiangxi University of Finance and Economics, Nanchang 330013, Jiangxi, China;2. Department of Industrial Systems Engineering and Management, National University of Singapore, 1 Engineering Drive 2, Singapore 117576, Singapore;3. Department of Computer Science, Xiamen University, Xiamen 361005, China;4. Faculty of Engineering, The University of Hong Kong, Pokfulam, Hong Kong;5. City University of Hong Kong Shenzhen Research Institute (CityUSRI), Shenzhen, China |
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| Abstract: | In this work, we investigate transit time in transportation service procurement, which is conducted by shippers using auctions to purchase transportation service from carriers in the planning stage. Besides cost, we find that many shippers are most concerned with transit time in practice; shorter transit time indicates better transportation service. To minimize both the total cost and transit time, the problem faced by shippers is the biobjective transportation service procurement problem with transit time. To solve the problem, we introduce a biobjective integer programming model that can also accommodate some important business constraints. A biobjective branch-and-bound algorithm that finds all extreme supported nondominated solutions is developed. To speed up the algorithm, two fast feasibility checks, a network flow model for particular subproblems, and lower bounds from relaxation are proposed. In addition, a sophisticated heuristic is introduced to meet shipper’s requirements in some situations. Computational experiments on evaluating the performance of the algorithms are conducted on a set of test instances that are generated from practical data. |
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