Complete results corresponding to the research presented in the paper entitled 'A compact reformulation of the two-stage robust resource-constrained project scheduling problem', submitted to 'Computers and Operations Research' in April 2020 (Bold and Goerigk, 2020).
The uncertain resource-constrained project scheduling problem (RCPSP) test instances on which these results are obtained are derived from deterministic instances in the PSPLIB (http://www.om-db.wi.tum.de/psplib/) involving 30 activities (j30). 3 robust counterparts corresponding to the delaying of (Gamma=) 3, 5 and 7 activities respectively have been generated for each of the 480 deterministic PSPLIB instances. Hence, a total of 1440 test instances have been generated.
This data set contains four data files corresponding to the results of four variants of the model proposed in Bold and Goerigk (2020). These are a 'basic' model (basic_results_full.txt), and three extended models: including transitivity constraints (trans_results_full.txt), warm-start (warmstart_results_full.txt), transitivity constraints plus warm-start (warmstarttrans_results_full.txt). See Bold and Goerigk (2020) for details of these methods.
Each data set reports for each instance the instance number (corresponding to the deterministic PSPLIB instance), the number of activities delayed (Gamma), the Gurobi solution status code, the best lower and upper-bound found by the solver, the gap between these two values, and the CPU run-time for that instance.
Results show that the proposed model out-performs the current state-of-the-art algorithms for solving the two-stage robust resource-constrained project scheduling problem, being much quicker to solve, and reaching optimality for 50% more instances on the same benchmark set.
Here is the main data that I used in the current study, including two binary format files, two Grads data descriptor files and two text files.
1, 5-year_annual _mean_pm25.grd is a binary file, which contains 5-year annual mean PM2.5 concentration across China from 2013 to 2017, the corresponding Grads data descriptor file is 5-year_annual_mean_pm25.ctl.
2, total_deaths is also a binary file, which contains total premature deaths attributable to 5-year annual mean PM2.5 concentration across China, the corresponding Grads data descriptor file is total_death.ctl.
3, provincial acute total deaths is a text file, which is the acute total deaths attributable to 5-year daily mean PM2.5 concentration on a provincial level.
4, provincial chronic deaths is also a text file, which is the chronic premature deaths attributable to 5-year annual mean PM2.5 concentration for 5 different health endpoints on a provincial level.