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Optimisation of Transportation Service Network Using -Node Large Bai, R., Woodward, J. R., Subramanian, N., & Cartlidge, J. (2018). Optimisation of transportation service network using k-node large neighbourhood search. Computers and Operations Research, 89, 193-205. https://doi.org/10.1016/j.cor.2017.06.008 Peer reviewed version License (if available): CC BY Link to published version (if available): 10.1016/j.cor.2017.06.008 Link to publication record in Explore Bristol Research PDF-document This is the author accepted manuscript (AAM). The final published version (version of record) is available online via Elsevier at http://www.sciencedirect.com/science/article/pii/S0305054817301466?via%3Dihub#!. Please refer to any applicable terms of use of the publisher. University of Bristol - Explore Bristol Research General rights This document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available: http://www.bristol.ac.uk/red/research-policy/pure/user-guides/ebr-terms/ ARTICLE IN PRESS JID: CAOR [m5G; June 15, 2017;19:2 ] Computers and Operations Research 0 0 0 (2017) 1–13 Contents lists available at ScienceDirect Computers and Operations Research journal homepage: www.elsevier.com/locate/cor Optimisation of transportation service network using κ-node large neighbourhood search ∗ Ruibin Bai a, , John R. Woodward b, Nachiappan Subramanian c, John Cartlidge a a School of Computer Science, Artificial Intelligence and Optimisation Research Group, University of Nottingham Ningbo China, China b School of Computing Science and Mathematics, University of Stirling, Scotland, United Kingdom c University of Sussex, UK a r t i c l e i n f o a b s t r a c t Article history: The Service Network Design Problem (SNDP) is generally considered as a fundamental problem in trans- Received 30 April 2015 portation logistics and involves the determination of an efficient transportation network and correspond- Revised 6 June 2017 ing schedules. The problem is extremely challenging due to the complexity of the constraints and the Accepted 7 June 2017 scale of real-world applications. Therefore, efficient solution methods for this problem are one of the Available online xxx most important research issues in this field. However, current research has mainly focused on various Keywords: sophisticated high-level search strategies in the form of different local search metaheuristics and their Logistics hybrids. Little attention has been paid to novel neighbourhood structures which also play a crucial role Transportation network in the performance of the algorithm. In this research, we propose a new efficient neighbourhood struc- Service network design ture that uses the SNDP constraints to its advantage and more importantly appears to have better reach- Metaheuristics ability than the current ones. The effectiveness of this new neighbourhood is evaluated in a basic Tabu Large neighbourhood search Search (TS) metaheuristic and a basic Guided Local Search (GLS) method. Experimental results based on a set of well-known benchmark instances show that the new neighbourhood performs better than the previous arc-flipping neighbourhood. The performance of the TS metaheuristic based on the proposed neighbourhood is further enhanced through fast neighbourhood search heuristics and hybridisation with other approaches. ©2017 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license. ( http://creativecommons.org/licenses/by/4.0/ ) 1. Introduction planning for less-than truck load transport and express deliveries where consolidation is necessary to improve the efficiency. It in- E-commerce and online shopping have rapidly transformed the volves the determination of a cost-effective transportation network formats of businesses in recent years. Online shopping companies and the services which it will provide, while satisfying the con- like Amazon.com and China-based Taobao.com have seen sig- straints related to geographically and temporally diverse demands, nificant growth in sales in recent years. While most companies are network availability, assets capacity, etc. The SNDP is strongly NP- keen to leverage new business opportunities such as online shop- Hard ( Ghamlouche et al., 2003 ) and hence it is impractical to op- ping, many of them also encounter new issues, such as providing timally solve the problem of realistic sizes. In fact, the SNDP is high quality delivery of billions of products. Hence the problem of generally of large-scale, due to the size of potential network. This logistics has received increasing attention from both industry and is particularly the case when the formulation is based on a time- the research communities. space network in which each node and each arc has a copy in each Freight transportation has great potential for further improve- period of the scheduling horizon (see Fig. 1 ). ment in efficiency and service level in the era of big data and Various heuristic and metaheuristic approaches have been ap- cloud computing. The Service Network Design Problem (SNDP) is plied to this problem and substantial progress has been made widely considered as the core problem of freight transportation ( Andersen et al., 2011; Bai et al., 2012; Chouman and Crainic, 2014; Crainic et al., 20 0 0; Ghamlouche et al., 20 03; 20 04; Hoff et al., 2010; Minh et al., 2013; Pedersen et al., 2009 ). However, almost ∗ Corresponding author. all of these research studies have focused on various intelligent E-mail addresses: [email protected] (R. Bai), high-level strategies for better trade-offs between search explo- [email protected] (J.R. Woodward), [email protected] rations and exploitations. Here, we consider high-level strategies (N. Subramanian), [email protected] (J. Cartlidge). http://dx.doi.org/10.1016/j.cor.2017.06.008 0305-0548/© 2017 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license. ( http://creativecommons.org/licenses/by/4.0/ ) Please cite this article as: R. Bai et al., Optimisation of transportation service network using κ-node large neighbourhood search, Com- puters and Operations Research (2017), http://dx.doi.org/10.1016/j.cor.2017.06.008 ARTICLE IN PRESS JID: CAOR [m5G; June 15, 2017;19:2 ] 2 R. Bai et al. / Computers and Operations Research 0 0 0 (2017) 1–13 day 1 day 2 day 3 day 4 day 5 day 6 day 7 CMND. Experiments with a simple TS framework demonstrated the superiority of the method to the earlier pivot-like neighbour- n1 hood functions in Crainic et al. (20 0 0) . This approach was later enhanced by adopting a path-relinking mechanism ( Ghamlouche et al., 2004 ). n2 Barnhart et al. (2002) addressed a real-life air cargo express delivery SNDP. The problem instances are characterised by their large sizes and the addition of further complex constraints to those n3 in the general SNDP model. A tree formulation was introduced and the problem was solved heuristically using a method based on column generation. Armacost et al. (2002) introduced a new mathematical model based on an innovative concept called the Fig. 1. An example of a time-space network with 3 nodes and 7 periods. composite variable , which has a better Linear Programming bound than other models. A column generation method using this new as domain-independent heuristic approaches that do not take spe- model was able to solve the problem successfully within a reason- cific advantage of a problem’s underlying low-level solution struc- able computational time, taking advantage of the specific problem ture. Examples of high-level strategies for more efficient search in- details. However, it may be difficult to generalise their model to clude the tabu-assisted guided local search by Bai et al. (2012) and other freight transportation applications, especially when there are the hybrid tabu search with path-relinking method by Minh et al. several classes of services being planned simultaneously. Pedersen (2013) . Analysis of the problem solution structure and its con- et al. (2009) studied more generic SNDP in which a set of asset straints is very limited. As indicated in Kendall et al. (2016) , a lot of balance constraints was added to model the requirements that the optimization research studies merely borrow different metaphors number of incoming vehicles at each node must equal to the out- without much deep insights on algorithmic or problem properties. going vehicles in order to maintain the continuity of freight ser- These approaches do not satisfy real-world requirements either vices over time. A multi-start metaheuristic, based on TS, was de- in terms of solution quality delivered or in computational time veloped and shown to outperform a commercially available MIP required. This is because the SNDP contains some difficult con- solver when computational time was limited to one hour per in- straints and a flow distribution sub-problem, generally referred to stance. Andersen et al. (2009) compared the node-arc based for- as the Capacitated Multicommodity Min-Cost Flow (CMMCF) prob- mulation, the path-based formulation and a cycle-based formu- lem, which can be very expensive to solve if it is called many times lation for SNDPs. Computational results on a set of small ran- within an iterative metaheuristic approach. This motivates us to domly generated instances indicated that the cycle-based formu- develop more efficient metaheuristics for this important and chal- lation gave significantly stronger bounds and hence may allow for lenging sub-problem. Therefore, unlike the above papers which fo- much faster solution methods of problems. More recent work by cus on high-level strategies, in this paper, we propose and study Bai et al. (2012) attempted to further reduce the computational a new larger neighbourhood that exploits the special structure of time and investigated a Guided Local Search (GLS) based hybrid the SNDP constraints and has much better reachability due to the approach.
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