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Decision-Focused Learning: Through the Lens of Learning to Rank
Decision-focused learning involves optimization problems, where the optimization parameters are defined partially. The goal is to predict the apriori unknown coefficient vector... -
Continuous Relaxation Annealing for Combinatorial Optimization
The dataset used in this paper is a collection of combinatorial optimization problems, including MIS and MaxCut problems on random regular graphs (RRGs) with varying degrees. -
Combinatorial 3D Shape Generation via Sequential Assembly
Combinatorial 3D shape generation framework using Bayesian optimization -
Learning Combinatorial Optimization Algorithms over Graphs
A dataset for learning combinatorial optimization algorithms over graphs. -
Pattern Reduction Dataset
The dataset is used to predict the final objective function value of a difficult combinatorial optimization problem from the input. -
Minimum Spanning Tree
The dataset used in the paper is the Minimum Spanning Tree problem, a combinatorial optimization problem where the goal is to find a minimum spanning tree of a graph. -
GenCO: Generating Diverse Designs with Combinatorial Constraints
GenCO: Generating Diverse Designs with Combinatorial Constraints -
Restricted Boltzmann Machine for Combinatorial Optimization and Integer Facto...
The dataset used in this paper is a Restricted Boltzmann Machine (RBM) for combinatorial optimization and integer factorization. -
Set Covering
The dataset is used to evaluate the performance of the proposed method. -
Multiple Knapsack Problem
The dataset is used to evaluate the performance of the proposed method. -
Traveling Salesman Problem
The Traveling Salesman Problem (TSP) is a classic problem in combinatorial optimization and operations research that involves finding the shortest possible tour that visits each... -
Flexible Job-Shop Scheduling Problem
The Flexible Job-Shop Scheduling Problem (FJSSP) is a combinatorial optimization problem where the goal is to find the optimal schedule for a set of jobs on a set of machines. -
Vehicle Routing Problem
The Vehicle Routing Problem (VRP) is a classic problem in combinatorial optimization. The problem is to find the shortest route that visits each node in a graph exactly once and... -
HIFF Function
The dataset used in the paper is a collection of combinatorial optimization problems, including concatenated deceptive traps, NK landscapes, and the HIFF function. -
NK Landscapes
The dataset used in the paper is a collection of combinatorial optimization problems, including concatenated deceptive traps, NK landscapes, and the HIFF function. -
SC, MIS, CA, and MC datasets
The dataset used in this paper is a collection of four NP-hard benchmark problems: Set Covering (SC), Maximal Independent Set (MIS), Combinatorial Auction (CA), and Maximum Cut...
