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Instance data for the paper Wirth, M., & Emde, S. (2018). Scheduling trucks on factory premises. Computers & Industrial Engineering, 126, 175-186. Every instance is in a separate text file, of which there are 54 in total (18 small, medium, and large instances, respectively). The data format is as follows. <num> is the running index of the instance. <NumTrucks> is the total number of trucks (jobs). <NumDoors> is the total number of dock doors (machines) on the factory premises. <MaxDoors> denotes the maximum number of doors to be visited per truck. <FactoryLength> denotes the size of the factory premises in meters (used to calculate the distances). <Distribution> is the type of probability distribution used for generating the processing and transfer times. <Processing> is a binary matrix signalling if a truck requires processing at a door: if and only if the entry in line i and column j is 1, truck j requires processing at door i. <ProcessingTime> is the processing time matrix: the entry in line i and column j is the processing time of truck j at door i. <DoorDistance> is the distance matrix between doors. The entrance / exit dummy door is the first line / column. <ReleaseDate> is the release date vector for the trucks. <DueDate> are the due dates of the trucks. <Cost> are the weights in the objective for each truck.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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