New hard set

Submitted by mario.vanhouck… on Mon, 08/19/2019 - 14:02

 

Going to the core

We have created in our latest paper "Going to the core of hard resource-constrained project scheduling instances", a new hard set of 623 instances -  which we refer to as the CV set - that you can download here. The paper is published in Computers and Operations Research in 2020 with the title "Going to the core of hard resource-constrained project scheduling instances". This dataset is the result of a study done by José Coelho and Mario Vanhoucke published in the “Computers and Operations Research” journal. Download the problem instances, solve them, and report your results on our website.

Publication: Coelho, J., & Vanhoucke, M. (2020). Going to the core of hard resource-constrained project scheduling instances. Computers and Operations Research, 121, 104976.

Website: https://www.projectmanagement.ugent.be/research/data/hardset

Dataset: Download

Other relevant publications:

1. HOW TO UPLOAD AND DOWNLOAD DATA?
See how you can upload and download solutions to our website using SolutionsUpdate.

Publication: Vanhoucke, M., & Coelho, J. (2018). A tool to test and validate algorithms for the resource-constrained project scheduling problem. Computers and Industrial Engineering, 118, 251–265
Website: http://solutionsupdate.ugent.be

2. SUMMARY OF DATASETS
See a summary of our datasets (not including the NetRes and CV sets)

Publication: Vanhoucke, M., Coelho, J., & Batselier, J. (2016). An overview of project data for integrated project management and control. Journal of Modern Project Management, 3(2), 6–21.
Website: https://www.projectmanagement.ugent.be/research/data

3. SOLVING THE INSTANCES (RCPSP)

We have programmed all existing branch-and-bound procedures to solve the resource-constrained project scheduling problem (RCPSP) and wrote a paper. The results of our computational tests are available on the “Solutions Update” website

Publication: Coelho, J., & Vanhoucke, M. (2018). An exact composite lower bound strategy for the resource-constrained project scheduling problem. Computers and Operations Research, 93, 135–150. https://doi.org/10.1016/j.cor.2018.01.017