A microcomputer based decision support tool for assigning dock doors in freight yards
Proceedings of the 12th annual conference on Computers and industrial engineering
An optimal solution to a dock door assignment problem
Proceedings of the 14th annual conference on Computers and industrial engineering
The Effects of Trailer Scheduling on the Layout of Freight Terminals
Transportation Science
The Best Shape for a Crossdock
Transportation Science
Minimizing makespan in two-stage hybrid cross docking scheduling problem
Computers and Operations Research
Truck dock assignment problem with operational time constraint within crossdocks
IEA/AIE'06 Proceedings of the 19th international conference on Advances in Applied Artificial Intelligence: industrial, Engineering and Other Applications of Applied Intelligent Systems
ICCSA'06 Proceedings of the 2006 international conference on Computational Science and Its Applications - Volume Part III
Hi-index | 0.01 |
This paper studies truck scheduling in a resource-constrained crossdock. The problem decides on the sequence of incoming and outgoing trucks at the dock doors of the crossdocking terminal, subject to the availability of crossdock resources including dock doors and material handling systems. The resources are assumed non-preemptive making it necessary to address the feasibility of the problem before its optimality as it might be entrapped in deadlock and no feasible solution is produced. The paper thus aims at developing an algorithmic approach capable of establishing solution feasibility for truck scheduling problem instances of various types and difficulty levels which at the same time can be readily implemented in an industrial setting. The proposed approach is a two-phase heuristic algorithm where in the first phase, a heuristic search is deployed to construct a feasible sequence of trucks for the assignment to dock doors and in the second, a rule-based heuristic is used to assign each sequenced truck to a proper dock door, subject to a limited number of forklifts, such that significant savings in the truck schedule length are achieved. Extensive experiments are conducted to evaluate the efficiency of the algorithm in terms of deadlock avoidance and solution quality. The evaluation is carried out against the solutions generated by the exact mathematical model of the problem and a constructive heuristic developed for a similar truck scheduling problem. Experimental results demonstrate that the proposed algorithm is robust in avoiding deadlock and generates feasible solutions for the instances where the other two approaches cannot. Furthermore, significant improvement in the solution quality is achieved by augmenting the algorithm to a re-starting heuristic.