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We study several stochastic combinatorial problems, including the expected utility maximization problem, the stochastic knapsack problem and the stochastic bin packing problem. A common technical challenge in these problems is to optimize…

Data Structures and Algorithms · Computer Science 2013-03-20 Jian Li , Wen Yuan

In the knapsack problem, we are given a knapsack of some capacity and a set of items, each with a size and a value. The goal is to pack a selection of these items fitting the knapsack that maximizes the total value. The online version of…

Data Structures and Algorithms · Computer Science 2024-02-29 Hans-Joachim Böckenhauer , Fabian Frei , Peter Rossmanith

Sequence partition problems arise in many fields, such as sequential data analysis, information transmission, and parallel computing. In this paper, we study the following partition problem variant: given a sequence of $n$ items…

Data Structures and Algorithms · Computer Science 2022-10-12 Kai Jin , Danna Zhang , Canhui Zhang

M.Aleknovich et al. have recently proposed a model of algorithms, called BT model, which generalizes both the priority model of Borodin, Nielson and Rackoff, as well as a simple dynamic programming model by Woeginger. BT model can be…

Computational Complexity · Computer Science 2007-12-25 Xin Li , Tian Liu

In the knapsack problems with neighborhood constraints that were studied before, the input is a graph $\mathcal{G}$ on a set $\mathcal{V}$ of items, each item $v \in \mathcal{V}$ has a weight $w_v$ and profit $p_v$, the size $s$ of the…

Data Structures and Algorithms · Computer Science 2025-04-25 Palash Dey , Ashlesha Hota , Sudeshna Kolay

The maximum bipartite matching problem is among the most fundamental and well-studied problems in combinatorial optimization. A beautiful and celebrated combinatorial algorithm of Hopcroft and Karp (1973) shows that maximum bipartite…

Data Structures and Algorithms · Computer Science 2023-12-21 Julia Chuzhoy , Sanjeev Khanna

We give a randomized online algorithm that guarantees near-optimal $\widetilde O(\sqrt T)$ expected swap regret against any sequence of $T$ adaptively chosen Lipschitz convex losses on the unit interval. This improves the previous best…

Machine Learning · Computer Science 2026-02-10 Lunjia Hu , Jon Schneider , Yifan Wu

The Time-Invariant Incremental Knapsack problem (IIK) is a generalization of Maximum Knapsack to a discrete multi-period setting. At each time, capacity increases and items can be added, but not removed from the knapsack. The goal is to…

Data Structures and Algorithms · Computer Science 2018-01-31 Yuri Faenza , Igor Malinovic

Given a multiset $S$ of $n$ positive integers and a target integer $t$, the Subset Sum problem asks to determine whether there exists a subset of $S$ that sums up to $t$. The current best deterministic algorithm, by Koiliaris and Xu…

Data Structures and Algorithms · Computer Science 2020-01-03 Ce Jin , Hongxun Wu

Given a convex function $f$ on $\mathbb{R}^n$ with an integer minimizer, we show how to find an exact minimizer of $f$ using $O(n^2 \log n)$ calls to a separation oracle and $O(n^4 \log n)$ time. The previous best polynomial time algorithm…

Data Structures and Algorithms · Computer Science 2023-11-15 Haotian Jiang , Yin Tat Lee , Zhao Song , Lichen Zhang

We provide faster randomized algorithms for computing an $\epsilon$-optimal policy in a discounted Markov decision process with $A_{\text{tot}}$-state-action pairs, bounded rewards, and discount factor $\gamma$. We provide an…

Machine Learning · Computer Science 2024-05-22 Yujia Jin , Ishani Karmarkar , Aaron Sidford , Jiayi Wang

In distribution compression, one aims to accurately summarize a probability distribution $\mathbb{P}$ using a small number of representative points. Near-optimal thinning procedures achieve this goal by sampling $n$ points from a Markov…

Machine Learning · Statistics 2022-10-19 Abhishek Shetty , Raaz Dwivedi , Lester Mackey

We consider the {\em correlated knapsack orienteering} (CSKO) problem: we are given a travel budget $B$, processing-time budget $W$, finite metric space $(V,d)$ with root $\rho\in V$, where each vertex is associated with a job with possibly…

Data Structures and Algorithms · Computer Science 2024-12-02 David Aleman Espinosa , Chaitanya Swamy

Packing problems are an important class of optimization problems. The probably most well-known problem if this type is knapsack and many generalizations of it have been studied in the literature like Two-dimensional Geometric Knapsack…

Data Structures and Algorithms · Computer Science 2019-11-26 Tobias Mömke , Andreas Wiese

We consider the chance-constrained binary knapsack problem (CKP), where the item weights are independent and normally distributed. We introduce a continuous relaxation for the CKP, represented as a non-convex optimization problem, which we…

Optimization and Control · Mathematics 2024-03-12 Junyoung Kim , Kyungsik Lee

We consider a dynamic assortment selection problem where a seller has a fixed inventory of $N$ substitutable products and faces an unknown demand that arrives sequentially over $T$ periods. In each period, the seller needs to decide on the…

Machine Learning · Computer Science 2024-01-25 Abdellah Aznag , Vineet Goyal , Noemie Perivier

In the Maximum Independent Set of Objects problem, we are given an $n$-vertex planar graph $G$ and a family $\mathcal{D}$ of $N$ objects, where each object is a connected subgraph of $G$. The task is to find a subfamily $\mathcal{F}…

Computational Geometry · Computer Science 2023-11-01 Jana Cslovjecsek , Michał Pilipczuk , Karol Węgrzycki

We consider fast algorithms for monotone submodular maximization with a general matroid constraint. We present a randomized $(1 - 1/e - \epsilon)$-approximation algorithm that requires $\tilde{O}_{\epsilon}(\sqrt{r} n)$ independence oracle…

Data Structures and Algorithms · Computer Science 2024-05-02 Yusuke Kobayashi , Tatsuya Terao

We consider a classical scheduling problem on $m$ identical machines. For an arbitrary constant $q>1$, the aim is to assign jobs to machines such that $\sum_{i=1}^m C_i^q$ is minimized, where $C_i$ is the total processing time of jobs…

Computational Complexity · Computer Science 2021-07-14 Lin Chen , Liangde Tao , José Verschae

The set of 2-dimensional packing problems builds an important class of optimization problems and Strip Packing together with 2-dimensional Bin Packing and 2-dimensional Knapsack is one of the most famous of these problems. Given a set of…

Discrete Mathematics · Computer Science 2019-02-07 Klaus Jansen , Malin Rau