Representative Solutions for Bi-Objective Optimisation
Authors: Emir Demirovi?, Nicolas Schwind1436-1443
AAAI 2020 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We implemented our algorithms and performed a numerical study. The goal was to verify the theoretical result and evaluate the empirical performance. |
| Researcher Affiliation | Academia | Emir Demirovi c School of Computing and Information Systems University of Melbourne Melbourne, Australia emir.demirovic@unimelb.edu.au Nicolas Schwind National Institute of Advanced Industrial Science and Technology Tokyo, Japan nicolas-schwind@aist.go.jp |
| Pseudocode | Yes | Algorithm 1: RS-Rp PF, Rq |
| Open Source Code | Yes | Our code and benchmarks are available online: bitbucket.org/Emir D/representative-solutions-for-biobjective-optimisation. |
| Open Datasets | Yes | Resource-constrained project scheduling problems with weighted earliness and tardiness objectives, labelled as RCPSP-wet in the Mini Zinc Challenge 2016 and 2017. Generated large bi-objective set covering benchmarks. Similar instances were used in other singleand multiobjective works (Musliu 2006; Bergman and Cire 2016). |
| Dataset Splits | No | The paper uses benchmarks and instances (RCPSP-wet, set covering benchmarks) but does not specify any training, validation, or test dataset splits (e.g., percentages, sample counts, or cross-validation details). |
| Hardware Specification | Yes | Experiments were performed on a machine with an i77700HQ CPU @ 2.80GHz processor and 32 GB of RAM, running one instance at a time with a time limit of ten hours. |
| Software Dependencies | No | The paper mentions using 'Gurobi as the optimisation solver' and 'Mini Zinc', but it does not provide specific version numbers for these or other software dependencies. |
| Experiment Setup | Yes | Experiments were performed on a machine with an i77700HQ CPU @ 2.80GHz processor and 32 GB of RAM, running one instance at a time with a time limit of ten hours. We consider values r1, 2, 3, 4, 5s for k, the number of desired representative solutions. |