Problem instances for the parallel serial-batch scheduling problem with incompatible job families, sequence-dependent setup times, and arbitrary sizes
Description
The data set provides instances for the parallel serial-batch scheduling problem with incompatible job families, sequence-dependent setup times, and arbitrary sizes. The instances are classified by the following characteristics: - number of machines (m= 1, 3, 4, 5, or 10) - number of jobs (n= 15, 30, 60, 100, 200, or 400) - number of incompatible job families (q= 3, 5, 10, or 20) - distribution of jobs to families (jtfam= uniform distribution (UD) or normal distribution (ND)) - capacity requirement scenarios defining job sizes (crs=CRS1 with [1, 12], CRS2 with [1, 25], CRS3 with [1, 50], or CRS4 with [13, 38]) - setup time severity factor (eta= 0.25 or 0.75) - tardiness factor (tf= 0.3 or 0.6) - due date range factor (rdd= 0.5 or 2.5) The maximum batch capacity (bc) is set to 50 for all instances. Job processing times and weights are drawn from discrete uniform distributions with the parameters [1, 100] and [1, 10]. All the scheduling relevant data is given within the files, whereby each file represents one problem instance. A unique identifier is given by the filename and also in the text file itself. In addition, best known objective values for several solution methods are included. The set S1 contains small instances with up to 60 jobs, whereas set S2 contains large instances with up to 400 jobs. Because not all instance characteristics combinations are reasonable with regard to batch capacity requirement scenarios, instance sets are restricted to those combinations with a sufficiently large approximated number of batches per machine. The last value of the folder names indicates the number of instances with the corresponding characteristics). More details about the problem instances and solution methods are given in the research paper "Scheduling parallel serial-batch processing machines with incompatible job families, sequence-dependent setup times and arbitrary sizes".