Towards Automatic Dominance Breaking for Constraint Optimization Problems

Authors: Christopher Mears, Maria Garcia de la Banda

IJCAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental Experimental results show that the method is able to find several dominance relations and to generate effective dominance breaking constraints.
Researcher Affiliation Academia Christopher Mears and Maria Garcia de la Banda Faculty of IT, Monash University, Australia {chris.mears,maria.garciadelabanda}@monash.edu
Pseudocode No The paper describes its methods through textual explanations and examples rather than structured pseudocode or algorithm blocks.
Open Source Code No The paper mentions using open-source tools like Mini Zinc and Gecode but does not state that the code for the authors' proposed method is publicly available or provided.
Open Datasets Yes Table 1 shows the time in seconds to solve instances with 50 objects, with and without automatically generated dominance breaking constraints (instances are from [Chu and Stuckey, 2012]).
Dataset Splits No The paper evaluates its method on instances of constraint optimization problems and reports performance metrics, but does not specify any training, validation, or test dataset splits.
Hardware Specification No The paper mentions software used (Mini Zinc 2.0 compiler and Gecode 4.3.3) but does not provide any specific details about the hardware (e.g., CPU, GPU, memory) on which the experiments were conducted.
Software Dependencies Yes These and all other experiments use the Mini Zinc 2.0 compiler and Gecode 4.3.3.
Experiment Setup No The paper describes the methodology for generating dominance breaking constraints and provides evaluation results, but does not specify concrete experimental setup details such as hyperparameter values or system-level training configurations.