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The Partitioning Min-Max Weighted Matching (PMMWM) problem is an NP-hard problem that combines the problem of partitioning a group of vertices of a bipartite graph into disjoint subsets with limited size and the classical Min-Max Weighted…

Data Structures and Algorithms · Computer Science 2022-01-26 Yuxuan Wang , Jinyao Xie , Jiongzhi Zheng , Kun He

$ $In many optimization problems, a feasible solution induces a multi-dimensional cost vector. For example, in load-balancing a schedule induces a load vector across the machines. In $k$-clustering, opening $k$ facilities induces an…

Data Structures and Algorithms · Computer Science 2018-11-14 Deeparnab Chakrabarty , Chaitanya Swamy

In This paper we present a genetic algorithm for the multi-pickup and delivery problem with time windows (m-PDPTW). The m-PDPTW is an optimization vehicles routing problem which must meet requests for transport between suppliers and…

Neural and Evolutionary Computing · Computer Science 2010-09-28 Imen Harbaoui Dridi , Ryan Kammarti , Mekki Ksouri , Pierre Borne

The largest common embeddable subtree problem asks for the largest possible tree embeddable into two input trees and generalizes the classical maximum common subtree problem. Several variants of the problem in labeled and unlabeled rooted…

Data Structures and Algorithms · Computer Science 2018-05-03 Andre Droschinsky , Nils M. Kriege , Petra Mutzel

Recombining trinomial trees are a workhorse for modeling discrete-event systems in option pricing, logistics, and feedback control. Because each node stores a state-dependent quantity, a depth-$D$ tree naively yields $\mathcal{O}(3^{D})$…

Data Structures and Algorithms · Computer Science 2025-10-06 Ethan Torres , Ramavarapu Sreenivas , Richard Sowers

We introduce a class of budgeted prize-collecting covering subgraph problems. For an input graph with prizes on the vertices and costs on the edges, the aim of these problems is to find a connected subgraph such that the cost of its edges…

Optimization and Control · Mathematics 2021-08-05 Nicola Morandi , Roel Leus , Hande Yaman

We consider the $k$-prize-collecting Steiner tree problem. An instance is composed of an integer $k$ and a graph $G$ with costs on edges and penalties on vertices. The objective is to find a tree spanning at least $k$ vertices which…

Computational Complexity · Computer Science 2019-11-22 Lehilton Lelis Chaves Pedrosa , Hugo Kooki Kasuya Rosado

We study the task of finding good local optima in combinatorial optimization problems. Although combinatorial optimization is NP-hard in general, locally optimal solutions are frequently used in practice. Local search methods however…

Machine Learning · Statistics 2020-01-03 Uri Patish , Shimon Ullman

Optimal transport (OT) distances are finding evermore applications in machine learning and computer vision, but their wide spread use in larger-scale problems is impeded by their high computational cost. In this work we develop a family of…

Machine Learning · Statistics 2018-03-06 Brahim Khalil Abid , Robert M. Gower

Mastering deep reinforcement learning (DRL) proves challenging in tasks featuring scant rewards. These limited rewards merely signify whether the task is partially or entirely accomplished, necessitating various exploration actions before…

Machine Learning · Computer Science 2024-04-11 Guojian Wang , Faguo Wu , Xiao Zhang

The Moving Target Vehicle Routing Problem with Obstacles (MT-VRP-O) seeks trajectories for several agents that collectively intercept a set of moving targets. Each target has one or more time windows where it must be visited, and the agents…

Robotics · Computer Science 2026-05-25 Anoop Bhat , Geordan Gutow , Surya Singh , Zhongqiang Ren , Sivakumar Rathinam , Howie Choset

We study the combinatorial pure exploration problem Best-Set in stochastic multi-armed bandits. In a Best-Set instance, we are given $n$ arms with unknown reward distributions, as well as a family $\mathcal{F}$ of feasible subsets over the…

Machine Learning · Computer Science 2017-06-06 Lijie Chen , Anupam Gupta , Jian Li , Mingda Qiao , Ruosong Wang

The capacitated tree cover problem with edge loads is a variant of the tree cover problem, where we are given facility opening costs, edge costs and loads, as well as vertex loads. We try to find a tree cover of minimum cost such that the…

Data Structures and Algorithms · Computer Science 2024-04-17 Benjamin Rockel-Wolff

Deep neural networks based on reinforcement learning (RL) for solving combinatorial optimization (CO) problems are developing rapidly and have shown a tendency to approach or even outperform traditional solvers. However, existing methods…

Machine Learning · Computer Science 2024-05-24 Chaoyang Wang , Pengzhi Cheng , Jingze Li , Weiwei Sun

Preventing poaching through ranger patrols protects endangered wildlife, directly contributing to the UN Sustainable Development Goal 15 of life on land. Combinatorial bandits have been used to allocate limited patrol resources, but…

Artificial Intelligence · Computer Science 2022-05-12 Lily Xu , Arpita Biswas , Fei Fang , Milind Tambe

In the \emph{budgeted rooted node-weighted Steiner tree} problem, we are given a graph $G$ with $n$ nodes, a predefined node $r$, two weights associated to each node modelling costs and prizes. The aim is to find a tree in $G$ rooted at $r$…

Data Structures and Algorithms · Computer Science 2022-11-15 Gianlorenzo D'Angelo , Esmaeil Delfaraz

This paper demonstrates the applicability of the Quantum Walk-based Optimisation Algorithm(QWOA) to the Capacitated Vehicle Routing Problem (CVRP). Efficient algorithms are developedfor the indexing and unindexing of the solution space and…

Quantum Physics · Physics 2021-10-01 Tavis Bennett , Edric Matwiejew , Sam Marsh , Jingbo B. Wang

We consider a variant of the prize collecting Steiner tree problem in which we are given a \emph{directed graph} $D=(V,A)$, a monotone submodular prize function $p:2^V \rightarrow \mathbb{R}^+ \cup \{0\}$, a cost function $c:V \rightarrow…

Data Structures and Algorithms · Computer Science 2022-10-04 Gianlorenzo D'Angelo , Esmaeil Delfaraz , Hugo Gilbert

Several recent applications of optimal transport (OT) theory to machine learning have relied on regularization, notably entropy and the Sinkhorn algorithm. Because matrix-vector products are pervasive in the Sinkhorn algorithm, several…

Machine Learning · Statistics 2021-03-09 Meyer Scetbon , Marco Cuturi , Gabriel Peyré

We derive tight bounds on the expected weights of several combinatorial optimization problems for random point sets of size $n$ distributed among the leaves of a balanced hierarchically separated tree. We consider {\it monochromatic} and…

Discrete Mathematics · Computer Science 2013-07-29 Béla Csaba , Thomas A. Plick , Ali Shokoufandeh