78 datasets found

The dataset used in this study is a benchmark for evaluating the performance of memory-efficient optimizers.

The dataset used in the paper is a set of data for the optimal coordination of automated vehicles at intersections. It includes the state and control trajectories of the...

The dataset used in the paper is a set of rewards for a multi-armed bandit problem.

The dataset used in the paper is a grid of input values, xi ∈ {x0, x1,..., xN }, with corresponding function values and gradients.

The dataset used in this paper is a collection of logistic regression problems.

The dataset contains results for the security-constrained optimal power flow problem.

The dataset contains results for the security-constrained optimal power flow problem.

The dataset used in this paper is a collection of 36 parameters involving the layout-design of components of a class of power module, and performance factors in terms of control...

The CEC 2019 benchmarks are a set of test functions used to evaluate the performance of optimization algorithms.

The dataset instances for the backboard wiring problem are taken from QAPLIB.

The backboard wiring problem is an optimization problem that considers the placement of electronic elements on a computer backboard to minimize the total length of wires...

The dataset used in this paper is a set of data generated by solving the open loop OCP (2.1) for a set of (randomly sampled) initial conditions.

The dataset used in this paper is a set of data generated by solving the open loop OCP (2.1) for a set of (randomly sampled) initial conditions.

The dataset used in this paper is a collection of test cases for the PowerModelsITD.jl software.

The dataset used in this paper is a collection of IEEE transmission and distribution networks.

The dataset used in this paper is a collection of power flow formulations for integrated transmission-distribution (ITD) optimization problems.

The dataset used in this paper is a streamed longitudinal data set-up where the objective is to maximize, over time, the cumulative profit across a large number of customer...

The dataset is used for predicting solutions to a stochastic discrete optimization problem. It contains instances of the load planning problem (LPP) for double-stack intermodal...

The dataset is used for predicting solutions to a stochastic discrete optimization problem. It contains instances of the load planning problem (LPP) for double-stack intermodal...

The dataset used in the paper is a hyperspectral unmixing problem with a nonconvex constraint.