Tabu assisted guided local search approaches for freight service network design

Bai, Ruibin; Kendall, Graham; Qu, Rong; Atkin, Jason

doi:10.1016/j.ins.2011.11.028

Cited by 26 publications

(10 citation statements)

References 27 publications

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“…Since the majority of previous research efforts for M-Determ and M-Stoch1 have been focusing on metaheuristic approaches, for example tabu search (Pedersen et al, 2009) and guided local search (Bai et al, 2012) for M-Determ and variable neighbourhood search with fast approximations (Hoff et al, 2010) for MStoch1, we expect that similar approaches would also be suitable for M-Stoch2 although M-Stoch2 is much harder due to the additional rerouting variables.…”

Section: Solution Methodologymentioning

confidence: 99%

“…Therefore, it is important that the solution method does not take too long. Bai et al (2010Bai et al ( , 2012 investigated various mechanisms within a guided local search (GLS) framework to reduce the computational time. The experimental study, based on a set of popular benchmark instances, showed that the final algorithm proposed was able to reduce the computational time by one third without worsening the solution quality when compared with Pedersen et al (2009).…”

Section: Literature Reviewmentioning

confidence: 99%

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Stochastic service network design with rerouting

Bai

Wallace

et al. 2014

Transportation Research Part B: Methodological

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Service network design under uncertainty is fundamentally crucial for all freight transportation companies.The main challenge is to strike a balance between two conflicting objectives: low network setup costs and low expected operational costs. Together these have a significant impact on the quality of freight services.Increasing redundancy at crucial network links is a common way to improve network flexibility. However, in a highly uncertain environment, a single predefined network is unlikely to suit all possible future scenarios, unless it is prohibitively costly. Hence, rescheduling is often an effective alternative. In this paper, we proposed a new stochastic freight service network design model with vehicle rerouting options. The proposed model explicitly introduces a set of integer variables for vehicle rerouting in the second stage of the stochastic program. Although computationally more expensive, the resultant model provides more options (i.e. rerouting) and flexibility for planners to deal with uncertainties more effectively. The new model was tested on a set of instances adapted from the literature and its performance and characteristics are studied through both comparative studies and detailed analyses at the solution structure level. Implications for practical applications are discussed and further research directions are also provided.

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Section: Solution Methodologymentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Stochastic service network design with rerouting

Bai

Wallace

et al. 2014

Transportation Research Part B: Methodological

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“…In order to evaluate the performance of the scheme we propose, experiments have been carried out based on the service network design solutions from Bai et al (2012). Their solutions were obtained as results of experimental tests on a set of benchmark instances for service network design.…”

Section: Computational Results and Analysismentioning

confidence: 99%

A scheme for determining vehicle routes based on Arc-based service network design

Jiang

Bai

Atkin

et al. 2016

INFOR: Information Systems and Operational Research

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A note on versions:The version presented here may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher's version. Please see the repository url above for details on accessing the published version and note that access may require a subscription. Abstract-In freight transportation, less-than-truckload carriers often need to assign each vehicle a cyclic route so that drivers can come back home after a certain period of time. However, the NodeArc model for service network design addresses decisions on each arc and does not determine routes directly, although the vehicle balancing constraint ensures that the number of outgoing vehicles equals the number of incoming vehicles at each node. How to transform the optimized service network into a set of vehicle routes remains an important problem that has not yet been studied. In this paper, we propose a three-phase scheme to address this problem. In the first stage, we present an algorithm based on the depth-first search to find all of the different cyclic routes in a service network design solution. In the second stage, we propose to prune poor cyclic routes using real-life constraints so that a collection of acceptable vehicle routes can be obtained before route assignment. Some of the pruning can also be done in the first stage to speed up the proposed algorithm. In the third stage, we formulate the problem of selecting a set of cyclic routes to cover the entire network as a weighted set covering problem. The resulting model is formulated as an integer program and solved with IBM ILOG CPLEX solver. Experimental results on benchmark instances for service network design indicate the effectiveness of the proposed scheme which gives high-quality solutions in an efficient way.

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“…In contrast to the low-level hybridisation, where one component is a sub-routine of another (see for example [2,20,35]), the high-level relay hybridisation is where both components are self-contained optimisation engines which are executed sequentially -in our matheuristic even iteratively. The hybridisation implemented in our paper differs from the commonly used approach in the high-level hybridisation where an optimisation engine can affect the other components only by providing a starting point in the optimisation search (see for example [14,12,21,23]).…”

Section: Motivation and Comparison With The Existing Literaturementioning

confidence: 99%