Problem instances for scheduling jobs with time windows on unrelated parallel machines

The following dataset contains problem instances for the unrelated machine scheduling problem with job release dates and deadlines, which are used in the article "Tadumadze, G., Emde, S. & Diefenbach, H. Exact and heuristic algorithms for scheduling jobs with time windows on unrelated parallel machines. OR Spectrum 42, 461–497 (2020). https://doi.org/10.1007/s00291-020-00586-w". The problem instances are stored in table “instances”, where the columns of the table can be interpreted as follows: Problem_ID: n: ; m: ; w: ; r: ; d: ; p: ; The first 80 entries (Problem_ID between 1-80), contain discrete Berth-allocation problem instances, provided by “Jean-François Cordeau, Gilbert Laporte, Pasquale Legato, Luigi Moccia, (2005) Models and Tabu Search Heuristics for the Berth-Allocation Problem. Transportation Science 39(4):526-538. https://doi.org/10.1287/trsc.1050.0120” and additionally contain machine availability times, which are stored in the following columns: s: ; e: ; The following 270 entries (Problem_ID between 81-270) contain newly generated random problem instances with the instance generation scheme proposed by “Nicholas G. Hall, Marc E. Posner, (2001) Generating Experimental Data for Computational Testing with Machine Scheduling Applications. Operations Research 49(6):854-865. https://doi.org/10.1287/opre.49.6.854.10014”. The first 10 instances (Problem_ID between 81-90) are used for parameter tuning tests and the next 180 (Problem_ID between 91-270) instances for computational performance comparison. The last 30 entries (Problem_ID between 271-300) contain integrated truck and workforce scheduling problem instances with fixed workforce at each door, provided by “Giorgi Tadumadze, Nils Boysen, Simon Emde, Felix Weidinger (2019) Integrated truck and workforce scheduling to accelerate the unloading of trucks. European Journal of Operational Research 278(1):343-362. https://doi.org/10.1016/j.ejor.2019.04.024”. The detailed computational results for each instance, approach and objective function are reported in tables which are named with the following convention: "results__”