Optimality Benchmark for Combinatorial Optimization

This dataset is an optimality benchmark for 1 synthetic 3 real-world application scenarios:<br>1. A synthetic dataset2. Residential energy consumption3. Bike sharing4. Charging control of electric vehicles<br>The dataset consists of 1 million random network positioning of agents in a binary tree, which are used in the collective learning algorithm of I-EPOS to explore the learning capacity of the combinatorial landscape. This dataset can be used as reference of other heuristic algorithms and enhancements. <br>Besides random positioning, the dataset comes with 124 metrics that evaluate deterministic criteria for the agents' positioning. <br><br><br>