Scheduled service network design with resource acquisition and management

被引:24
|
作者
Crainic, Teodor Gabriel [1 ]
Hewitt, Mike [2 ]
Toulouse, Michel [3 ]
Duc Minh Vu [4 ]
机构
[1] Univ Quebec Montreal, CIRRELT Interuniv Res Ctr Enterprise Networks Log, Sch Management, CP 8888,Succ Ctr Ville, Montreal, PQ H3C 3P8, Canada
[2] Loyola Univ, Dept Informat Syst & Supply Chain Management, Quinlan Sch Business, Chicago, IL 60611 USA
[3] Vietnamese German Univ, Fac Engn, Binh Duong New City, Binh Duong Prov, Vietnam
[4] Loyola Univ, Quinlan Sch Business, Chicago, IL 60611 USA
基金
加拿大自然科学与工程研究理事会;
关键词
Service network design; Fleet sizing and management; Matheuristics; Slope scaling; Column generation;
D O I
10.1007/s13676-017-0103-x
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
We present a new planning model for freight consolidation carriers, one that links strategic, resource acquisition, and allocation decisions with tactical, service network design-related decisions. Specifically, such as service network design models that recognize resource constraints, the model selects services and routes both commodities and the resources needed to support the services that transport them. In addition, the model recognizes that resources can be grouped into types that differ from one another with respect to capabilities, e.g., speeds, capacities, scheduling rules, etc. Ultimately, along with recognizing resource constraints, the model also makes strategic decisions such as how many resources of each type should be acquired, to what terminal new resources should be assigned, and which existing terminal-based resources should be reassigned. As such, the model can be used from a strategic planning, resource acquisition, mixing, and allocation perspective as it provides an estimate of the impact of such decisions on transportation costs. We extend a matheuristic for a service network design problem with a fixed set (both in number and allocation) of resources of a single type to one that can also make these acquisition and allocation decisions for multiple types of resource. Then, with an extensive computational study, we demonstrate the efficacy of the matheuristic and benchmark its performance against both a leading commercial solver and a column generation-based heuristic. Finally, we perform an extensive computational study to understand how the resource-related and service network design-related components of the model interact, including how freight volumes and cost structures impact how many resources should beacquired.
引用
收藏
页码:277 / 309
页数:33
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