| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 494828 | Applied Soft Computing | 2015 | 19 Pages |
•This paper proposes a meta-heuristic based algorithm for scheduling inbound and outbound trucks in cross docking problems.•The proposed method lets the outbound trucks to intermittently move in and out of the dock during the time intervals between their task executions.•The numerical results reveal that the proposed method is superior to the method of Yu and Egbelu [1] from the view point of minimizing makespan.•Two heuristic algorithms of dynamic crossover for inbound and outbound trucks are provided.•Two heuristic algorithms of dynamic mutation for inbound and outbound trucks are provided.
Cross docking is a logistic concept in which product items are unloaded from inbound trucks into a warehouse and then are sorted out based on customer demands and loaded into outbound trucks. For a dock holding pattern for outbound trucks, two possible scenarios can be defined. In the first scenario, whenever a truck goes into a shipping dock, it does not leave the dock until all needed product items are loaded into outbound truck. In the second scenario, outbound trucks can enter and leave the dock repeatedly. Therefore, in the second scenario it is possible that an outbound truck loads some of its needed products from shipping dock, leaves the dock for another outbound truck, waits and goes into the shipping dock again to load all or part of its remaining product items. This paper proposes a genetic algorithm-based framework for scheduling inbound and outbound trucks in cross docking systems with temporary storage of product items at shipping dock for the second defined scenario such that minimizes total operation time. In order to show the merit of the proposed method in providing a sequence that minimizes the total operation time, the operation time of the proposed method is compared to a well-known existing model by several numerical examples. The numerical results show the high performance of the proposed algorithm.
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