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Found 8 papers, 1 papers with code
Evolutionary Multi-Objective Diversity Optimization
Creating diverse sets of high quality solutions has become an important problem in recent years.
Optimizing Chance-Constrained Submodular Problems with Variable Uncertainties
Chance constraints are frequently used to limit the probability of constraint violations in real-world optimization problems where the constraints involve stochastic components.
Analysis of Quality Diversity Algorithms for the Knapsack Problem
Quality diversity (QD) algorithms have been shown to be very successful when dealing with problems in areas such as robotics, games and combinatorial optimization.
Niching-based Evolutionary Diversity Optimization for the Traveling Salesperson Problem
In this work, we consider the problem of finding a set of tours to a traveling salesperson problem (TSP) instance maximizing diversity, while satisfying a given cost constraint.
Analysis of Evolutionary Diversity Optimisation for Permutation Problems
This work contributes to this line of research with an investigation on evolutionary diversity optimization for three of the most well-studied permutation problems, namely the Traveling Salesperson Problem (TSP), both symmetric and asymmetric variants, and Quadratic Assignment Problem (QAP).
Pareto Optimization for Subset Selection with Dynamic Partition Matroid Constraints
In this study, we consider the subset selection problems with submodular or monotone discrete objective functions under partition matroid constraints where the thresholds are dynamic.
Maximizing Submodular or Monotone Functions under Partition Matroid Constraints by Multi-objective Evolutionary Algorithms
Many important problems can be regarded as maximizing submodular functions under some constraints.
Evolving Diverse Sets of Tours for the Travelling Salesperson Problem
Evolving diverse sets of high quality solutions has gained increasing interest in the evolutionary computation literature in recent years.
