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In this paper, we propose a general framework to design {efficient} polynomial time approximation schemes (EPTAS) for fundamental stochastic combinatorial optimization problems. Given an error parameter $\epsilon>0$, such algorithmic…

Data Structures and Algorithms · Computer Science 2025-05-30 Danny Segev , Sahil Singla

Quality diversity (QD) algorithms have been shown to be very successful when dealing with problems in areas such as robotics, games and combinatorial optimization. They aim to maximize the quality of solutions for different regions of the…

Neural and Evolutionary Computing · Computer Science 2022-07-29 Adel Nikfarjam , Anh Viet Do , Frank Neumann

In the \textsc{2-Dimensional Knapsack} problem (2DK) we are given a square knapsack and a collection of $n$ rectangular items with integer sizes and profits. Our goal is to find the most profitable subset of items that can be packed…

Computational Geometry · Computer Science 2021-03-19 Waldo Gálvez , Fabrizio Grandoni , Arindam Khan , Diego Ramírez-Romero , Andreas Wiese

Knapsack problems are classic models that can formulate a wide range of applications. In this work, we deal with the Budgeted Maximum Coverage Problem (BMCP), which is a generalized 0-1 knapsack problem. Given a set of items with…

Artificial Intelligence · Computer Science 2020-07-14 Liwen Li , Zequn Wei , Jin-Kao Hao , Kun He

In resource allocation, we often require that the output allocation of an algorithm is stable against input perturbation because frequent reallocation is costly and untrustworthy. Varma and Yoshida (SODA'21) formalized this requirement for…

Data Structures and Algorithms · Computer Science 2024-05-24 Soh Kumabe , Yuichi Yoshida

The Subset Sum Ratio problem (SSR) asks, given a multiset $A$ of positive integers, to find two disjoint subsets of $A$ such that the largest-to-smallest ratio of their sums is minimized. In this paper we study the $k$-version of SSR,…

We study the standard-form ILP problem $\max\{ c^\top x \colon A x = b,\; x \in Z_{\geq 0}^n \}$, where $A\in Z^{k\times n}$ has full row rank. We obtain refined FPT algorithms parameterized by $k$ and $\Delta$, the maximum absolute value…

Data Structures and Algorithms · Computer Science 2026-04-16 Dmitry Gribanov , Tagir Khayaleyev , Mikhail Cherniavskii , Maxim Klimenko , Dmitry Malyshev , Stanislav Moiseev

Submodular maximization has been a central topic in theoretical computer science and combinatorial optimization over the last decades. Plenty of well-performed approximation algorithms have been designed for the problem over a variety of…

Data Structures and Algorithms · Computer Science 2023-07-20 Xiaoming Sun , Jialin Zhang , Zhijie Zhang

The mixing set with a knapsack constraint arises as a substructure in mixed-integer programming reformulations of chance-constrained programs with stochastic right-hand-sides over a finite discrete distribution. Recently, Luedtke et al.…

Optimization and Control · Mathematics 2012-07-05 Ahmad Abdi , Ricardo Fukasawa

Given an $n$-dimensional convex body by a membership oracle in general, it is known that any polynomial-time deterministic algorithm cannot approximate its volume within ratio $(n/\log n)^n$. There is a substantial progress on randomized…

Computational Complexity · Computer Science 2016-07-22 Ei Ando , Shuji Kijima

We introduce the subset assignment problem in which items of varying sizes are placed in a set of bins with limited capacity. Items can be replicated and placed in any subset of the bins. Each (item, subset) pair has an associated cost. Not…

Data Structures and Algorithms · Computer Science 2016-10-04 Shahram Ghandeharizadeh , Sandy Irani , Jenny Lam

We consider the problem of maximizing a fractionally subadditive function under a knapsack constraint that grows over time. An incremental solution to this problem is given by an order in which to include the elements of the ground set, and…

Data Structures and Algorithms · Computer Science 2023-05-25 Yann Disser , Max Klimm , Annette Lutz , David Weckbecker

In the classic $k$-center problem, we are given a metric graph, and the objective is to open $k$ nodes as centers such that the maximum distance from any vertex to its closest center is minimized. In this paper, we consider two important…

Data Structures and Algorithms · Computer Science 2013-01-16 Danny Z. Chen , Jian Li , Hongyu Liang , Haitao Wang

We consider the rooted orienteering problem in Euclidean space: Given $n$ points $P$ in $\mathbb R^d$, a root point $s\in P$ and a budget $\mathcal B>0$, find a path that starts from $s$, has total length at most $\mathcal B$, and visits as…

Data Structures and Algorithms · Computer Science 2022-04-22 Lee-Ad Gottlieb , Robert Krauthgamer , Havana Rika

We study the framework of a dynamic decision-making scenario with resource constraints. In this framework, an agent, whose target is to maximize the total reward under the initial inventory, selects an action in each round upon observing a…

Machine Learning · Computer Science 2024-12-19 Zhaohua Chen , Rui Ai , Mingwei Yang , Yuqi Pan , Chang Wang , Xiaotie Deng

We consider a bilevel continuous knapsack problem where the leader controls the capacity of the knapsack, while the follower chooses a feasible packing maximizing his own profit. The leader's aim is to optimize a linear objective function…

Data Structures and Algorithms · Computer Science 2022-07-19 Christoph Buchheim , Dorothee Henke , Jannik Irmai

We consider non-preemptive scheduling problems on parallel identical machines where machines change their status from being available to being unavailable and vice versa along the time horizon. The particular form of unavailability we…

Data Structures and Algorithms · Computer Science 2023-06-21 G. Jaykrishnan , Asaf Levin

Klee's Measure Problem (KMP) asks for the volume of the union of n axis-aligned boxes in d-space. Omitting logarithmic factors, the best algorithm has runtime O*(n^{d/2}) [Overmars,Yap'91]. There are faster algorithms known for several…

Computational Geometry · Computer Science 2013-06-13 Karl Bringmann

We study the problem of robustly learning multi-dimensional histograms. A $d$-dimensional function $h: D \rightarrow \mathbb{R}$ is called a $k$-histogram if there exists a partition of the domain $D \subseteq \mathbb{R}^d$ into $k$…

Machine Learning · Computer Science 2018-02-26 Ilias Diakonikolas , Jerry Li , Ludwig Schmidt

We study the three-dimensional Knapsack (3DK) problem, in which we are given a set of axis-aligned cuboids with associated profits and an axis-aligned cube knapsack. The objective is to find a non-overlapping axis-aligned packing (by…

Data Structures and Algorithms · Computer Science 2025-03-26 Klaus Jansen , Debajyoti Kar , Arindam Khan , K. V. N. Sreenivas , Malte Tutas
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