Finding Diverse Solutions of High Quality to Constraint Optimization Problems

Authors: Thierry Petit, Andrew C. Trapp

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

Reproducibility Variable Result LLM Response
Research Type Experimental 7 Experiments
Researcher Affiliation Academia Thierry Petit Foisie School of Business, Worcester Polytechnic Institute, USA Mines de Nantes / LINA, France tpetit@{wpi.edu,mines-nantes.fr} Andrew C. Trapp Foisie School of Business, Worcester Polytechnic Institute, USA atrapp@wpi.edu
Pseudocode Yes Algorithm 1: k BESTOPT(N, k, xδ, x Q): Solutions set S
Open Source Code No The paper does not provide concrete access to source code (specific repository link, explicit code release statement, or code in supplementary materials) for the methodology described in this paper.
Open Datasets Yes We implemented the chords musical benchmark [Truchet and Codognet, 2004; Petit, 2012]. We used a graph-variable model [Fages and Lorca, 2012] for solving TSPLIB symmetric instances [Reinelt, 1991], which are state-of-the-art routing benchmarks.
Dataset Splits No The paper does not provide specific dataset split information (exact percentages, sample counts, citations to predefined splits, or detailed splitting methodology) needed to reproduce the data partitioning.
Hardware Specification Yes We used an Intel Xeon 2.27GHz machine and the Choco 3.2.1 solver.
Software Dependencies Yes We used an Intel Xeon 2.27GHz machine and the Choco 3.2.1 solver.
Experiment Setup Yes We systematically re-use the search strategy of the original model (e.g., DOM/WDEG [Boussemart et al., 2004]), and then assign the new variables in static order. For each instance, we give average results obtained with 20 randomly generated cost matrices, and we generate 20 solutions per matrix and ratio, with a time-limit of 15 seconds for each new solution. Table 2 shows the results for 20 solutions per generated set, with a 5 minute time-limit, using NS.