scholarly journals A Combinatorial Benders’ Cuts Algorithm for the Local Container Drayage Problem

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Zhaojie Xue ◽  
Canrong Zhang ◽  
Peng Yang ◽  
Lixin Miao
Keyword(s):  
Vehicle Routing ◽  
Numerical Experiments ◽  
Operation Mode ◽  
Scheduling Problem ◽  
Temporal Constraints ◽  
Vehicle Routing And Scheduling ◽  
Routing And Scheduling ◽  
Empty Containers ◽  
Operation Cost

This paper examines the local container drayage problem under a special operation mode in which tractors and trailers can be separated; that is, tractors can be assigned to a new task at another location while trailers with containers are waiting for packing or unpacking. Meanwhile, the strategy of sharing empty containers between different customers is also considered to improve the efficiency and lower the operation cost. The problem is formulated as a vehicle routing and scheduling problem with temporal constraints. We adopt combinatorial benders’ cuts algorithm to solve this problem. Numerical experiments are performed on a group of randomly generated instances to test the performance of the proposed algorithm.

A Vehicle Routing and Scheduling Model for a Distribution Center

2010 ◽  
pp. 334-366 ◽  
Author(s):  
Hsiao-Fan Wang
Keyword(s):  
Vehicle Routing ◽  
Efficient Solution ◽  
Structural Model ◽  
Time Windows ◽  
Distribution Center ◽  
Multiple Time ◽  
Scheduling Problem ◽  
Vehicle Routing And Scheduling ◽  
Routing And Scheduling ◽  
Operation Cost

One key role along green supply chain is the distribution center which has the responsibility to deliver the commodities to the customers and collect the end-used products back to the center for further process. This activity requires a distributor to determine how many vehicles with what sizes along which routes to deliver commodities so that the demands from all customers will be satisfied within customers’ available time with minimum operation cost. This problem can be classified into a vehicle routing and scheduling problem with multiple vehicle types and service time windows. In practice, the complexity of the problem requires a structural model to facilitate general analysis and applications. However, also because of its complexity, an efficient solution procedure is equivalently important. Therefore, in this study, we have first developed a model for a distribution center to support the decisions on vehicle types and numbers; as well as the routing route and schedule so that the overall operation cost will be minimized. Since this model of vehicle routing and scheduling problem with multiple vehicle types and multiple time windows (VRSP-MVMT) is a nondeterministic polynomial time (NP)-hard problem, we have developed a genetic algorithm (GA) for efficient solution. The efficiency and accuracy of the algorithm will be evaluated and illustrated with numerical examples.

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