The freight allocation problem with all-units quantity-based discount: A heuristic algorithm
This paper studies a problem encountered by a buying office for one of the largest retail distributors in the world. An important task for the buying office is to plan the distribution of goods from Asia to various destinations across Europe. The goods are transported along shipping lanes by shippin...
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| Published in | Omega (Oxford) Vol. 40; no. 4; pp. 415 - 423 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Kidlington
Elsevier Ltd
01.08.2012
Elsevier Pergamon Press Inc |
| Series | Omega |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0305-0483 1873-5274 |
| DOI | 10.1016/j.omega.2011.05.005 |
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| Abstract | This paper studies a problem encountered by a buying office for one of the largest retail distributors in the world. An important task for the buying office is to plan the distribution of goods from Asia to various destinations across Europe. The goods are transported along shipping lanes by shipping companies, which offer different discount rates depending on the freight quantity. To increase the reliability of transportation, the shipper imposes a quantity limit on each shipping company on each shipping lane. To guarantee a minimum business volume, each shipping company requests a minimum total freight quantity over all lanes if it is contracted. The task involves allocating projected demand of each shipping lane to shipping companies subject to the above conditions such that the total cost is minimized.
Existing work on this and related problems employs commercial linear programming software to solve their models. However, since the problem is
N
P
−
hard
in the strong sense, it is unlikely to be solvable optimally in reasonable time for large cases. Hence, we propose the first heuristic-based algorithm for the problem, which combines a filter-and-fan search scheme with a tabu search mechanism. Experiments on randomly generated test instances show that as the size of the problem increases, our algorithm produces superior solutions in less time compared to a leading mixed-integer programming solver.
► Studied a freight allocation problem encountered by a major international retailer. ► Proposed a linear programming formulation for the problem. ► Devised the first heuristic solution for large practical instance. ► Generated benchmark data based on practical scenarios. ► Designed computational experiments to show the effectiveness of the approach. |
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| AbstractList | This paper studies a problem encountered by a buying office for one of the largest retail distributors in the world. An important task for the buying office is to plan the distribution of goods from Asia to various destinations across Europe. The goods are transported along shipping lanes by shipping companies, which offer different discount rates depending on the freight quantity. To increase the reliability of transportation, the shipper imposes a quantity limit on each shipping company on each shipping lane. To guarantee a minimum business volume, each shipping company requests a minimum total freight quantity over all lanes if it is contracted. The task involves allocating projected demand of each shipping lane to shipping companies subject to the above conditions such that the total cost is minimized. Existing work on this and related problems employs commercial linear programming software to solve their models. However, since the problem is NP-hard in the strong sense, it is unlikely to be solvable optimally in reasonable time for large cases. Hence, we propose the first heuristic-based algorithm for the problem, which combines a filter-and-fan search scheme with a tabu search mechanism. Experiments on randomly generated test instances show that as the size of the problem increases, our algorithm produces superior solutions in less time compared to a leading mixed-integer programming solver. [PUBLICATION ABSTRACT] This paper studies a problem encountered by a buying office for one of the largest retail distributors in the world. An important task for the buying office is to plan the distribution of goods from Asia to various destinations across Europe. The goods are transported along shipping lanes by shipping companies, which offer different discount rates depending on the freight quantity. To increase the reliability of transportation, the shipper imposes a quantity limit on each shipping company on each shipping lane. To guarantee a minimum business volume, each shipping company requests a minimum total freight quantity over all lanes if it is contracted. The task involves allocating projected demand of each shipping lane to shipping companies subject to the above conditions such that the total cost is minimized. Existing work on this and related problems employs commercial linear programming software to solve their models. However, since the problem is N P − hard in the strong sense, it is unlikely to be solvable optimally in reasonable time for large cases. Hence, we propose the first heuristic-based algorithm for the problem, which combines a filter-and-fan search scheme with a tabu search mechanism. Experiments on randomly generated test instances show that as the size of the problem increases, our algorithm produces superior solutions in less time compared to a leading mixed-integer programming solver. ► Studied a freight allocation problem encountered by a major international retailer. ► Proposed a linear programming formulation for the problem. ► Devised the first heuristic solution for large practical instance. ► Generated benchmark data based on practical scenarios. ► Designed computational experiments to show the effectiveness of the approach. This paper studies a problem encountered by a buying office for one of the largest retail distributors in the world. An important task for the buying office is to plan the distribution of goods from Asia to various destinations across Europe. The goods are transported along shipping lanes by shipping companies, which offer different discount rates depending on the freight quantity. To increase the reliability of transportation, the shipper imposes a quantity limit on each shipping company on each shipping lane. To guarantee a minimum business volume, each shipping company requests a minimum total freight quantity over all lanes if it is contracted. The task involves allocating projected demand of each shipping lane to shipping companies subject to the above conditions such that the total cost is minimized. |
| Author | Lim, Andrew Luo, Meifeng Gao, Xiang Qin, Hu |
| Author_xml | – sequence: 1 givenname: Hu surname: Qin fullname: Qin, Hu email: tigerqin@cityu.edu.hk organization: School of Management, Huazhong University of Science and Technology, No. 1037, Luoyu Road, Wuhan, China – sequence: 2 givenname: Meifeng surname: Luo fullname: Luo, Meifeng email: lgtmluo@polyu.edu.hk organization: Department of Logistics and Maritime Studies, Faculty of Business, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong – sequence: 3 givenname: Xiang surname: Gao fullname: Gao, Xiang email: gaoxiang@cityu.edu.hk organization: Department of Management Sciences, City University of Hong Kong, Tat Chee Ave, Kowloon Tong, Hong Kong – sequence: 4 givenname: Andrew surname: Lim fullname: Lim, Andrew email: lim.andrew@cityu.edu.hk organization: Department of Management Sciences, City University of Hong Kong, Tat Chee Ave, Kowloon Tong, Hong Kong |
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| Cites_doi | 10.1016/j.orl.2007.04.001 10.1287/trsc.1050.0123 10.1287/opre.42.1.14 10.1016/j.ejor.2003.08.021 10.1016/0377-2217(95)00315-0 10.1016/S0377-2217(02)00457-5 10.1002/1520-6750(200012)47:8<686::AID-NAV6>3.0.CO;2-W 10.1016/j.cor.2005.07.006 10.1057/jors.1994.189 10.1002/1520-6750(199303)40:2<255::AID-NAV3220400209>3.0.CO;2-G 10.1016/0377-2217(95)00169-7 10.1016/j.ejor.2007.12.035 10.1080/07408179708966342 10.1016/S0377-2217(99)00445-2 10.1016/j.omega.2007.09.002 10.1016/j.omega.2005.09.002 10.1007/s00291-006-0066-z 10.1287/inte.24.1.50 10.1016/S0377-2217(02)00407-1 10.1016/j.ejor.2007.01.019 10.1111/j.1937-5956.1998.tb00129.x 10.1016/j.omega.2009.09.003 10.1057/palgrave.jors.2602380 10.1016/j.cor.2008.05.003 10.1016/j.ejor.2006.03.010 10.1016/j.orl.2004.04.015 10.1023/A:1018999418377 10.1080/07408179808966518 |
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| Keywords | Tabu search Quantity discount Filter-and-fan Freight allocation Heuristic Costs Linear programming Mixed integer programming Experimental study Modeling Search algorithm Discounting Distributor Heuristic method NP hard problem Maritime transportation Reliability Contract Logistics |
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| SubjectTerms | Algorithms Applied sciences Discount rates Exact sciences and technology Filter-and-fan Freight Freight allocation Freight allocation Quantity discount Heuristic Filter-and-fan Tabu search Ground, air and sea transportation, marine construction Heuristic Heuristik Integer programming Internationaler Güterverkehr Lieferkette Linear programming Logistics Marine and water way transportation and traffic Mathematical programming Operational research and scientific management Operational research. Management science Operations Research Optimization algorithms Quantity discount Reliability theory. Replacement problems Shipping Studies Tabu search Transportproblem |
| Title | The freight allocation problem with all-units quantity-based discount: A heuristic algorithm |
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