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Packing problems are in general NP-hard, even for simple cases. Since now there are no highly efficient algorithms available for solving packing problems. The two-dimensional bin packing problem is about packing all given rectangular items,…

Neural and Evolutionary Computing · Computer Science 2020-07-28 Camelia-M. Pintea , Cristian Pascan , Mara Hajdu-Macelaru

In this paper three heuristic algorithms using the Divide-and-Conquer paradigm are developed and assessed for three integer optimizations problems: Multidimensional Knapsack Problem (d-KP), Bin Packing Problem (BPP) and Travelling Salesman…

Optimization and Control · Mathematics 2022-07-13 Fernando A Morales

Multi-armed bandit problems are the predominant theoretical model of exploration-exploitation tradeoffs in learning, and they have countless applications ranging from medical trials, to communication networks, to Web search and advertising.…

Data Structures and Algorithms · Computer Science 2017-09-06 Ashwinkumar Badanidiyuru , Robert Kleinberg , Aleksandrs Slivkins

We consider the problem of assigning students to schools, when students have different utilities for schools and schools have capacity. There are additional group fairness considerations over students that can be captured either by concave…

Data Structures and Algorithms · Computer Science 2025-04-24 Santhini K. A. , Kamesh Munagala , Meghana Nasre , Govind S. Sankar

The submodular knapsack problem (SKP), which seeks to maximize a submodular set function by selecting a subset of elements within a given budget, is an important discrete optimization problem. The majority of existing approaches to solving…

Data Structures and Algorithms · Computer Science 2025-07-16 Yimin Hao , Yi Zhou , Chao Xu , Zhang-Hua Fu

Benchmark instances for the unbounded knapsack problem are typically generated according to specific criteria within a given constant range $R$, and these instances can be referred to as the unbounded knapsack problem with bounded…

Data Structures and Algorithms · Computer Science 2024-03-19 Yang Yang

Evolutionary multi-objective algorithms have been widely shown to be successful when utilized for a variety of stochastic combinatorial optimization problems. Chance constrained optimization plays an important role in complex real-world…

Neural and Evolutionary Computing · Computer Science 2023-03-06 Kokila Perera , Aneta Neumann , Frank Neumann

In the incremental knapsack problem ($\IK$), we are given a knapsack whose capacity grows weakly as a function of time. There is a time horizon of $T$ periods and the capacity of the knapsack is $B_t$ in period $t$ for $t = 1, \ldots, T$.…

Data Structures and Algorithms · Computer Science 2013-11-20 Daniel Bienstock , Jay Sethuraman , Chun Ye

In this paper, we consider the classic stochastic (dynamic) knapsack problem, a fundamental mathematical model in revenue management, with general time-varying random demand. Our main goal is to study the optimal policies, which can be…

Optimization and Control · Mathematics 2018-07-19 Yingdong Lu

The Bilevel Optimization Problem is a hierarchical optimization problem with two agents, a leader and a follower. The leader make their own decisions first, and the followers make the best choices accordingly. The leader knows the…

Artificial Intelligence · Computer Science 2023-12-12 Sunhyeon Kwon , Hwayong Choi , Sungsoo Park

Computing sets of high quality solutions has gained increasing interest in recent years. In this paper, we investigate how to obtain sets of optimal solutions for the classical knapsack problem. We present an algorithm to count exactly the…

Data Structures and Algorithms · Computer Science 2021-06-15 Jakob Bossek , Aneta Neumann , Frank Neumann

We explore a multiple-stage variant of the min-max robust selection problem with budgeted uncertainty that includes queries. First, one queries a subset of items and gets the exact values of their uncertain parameters. Given this…

Optimization and Control · Mathematics 2025-01-07 Xiaoyu Chen , Marc Goerigk , Michael Poss

The typical algorithmic problem in viral marketing aims to identify a set of influential users in a social network, who, when convinced to adopt a product, shall influence other users in the network and trigger a large cascade of adoptions.…

Machine Learning · Computer Science 2014-04-17 Nan Du , Yingyu Liang , Maria Florina Balcan , Le Song

We study the problem of clustering a set of items from binary user feedback. Such a problem arises in crowdsourcing platforms solving large-scale labeling tasks with minimal effort put on the users. For example, in some of the recent…

Machine Learning · Statistics 2024-12-20 Kaito Ariu , Jungseul Ok , Alexandre Proutiere , Se-Young Yun

We consider binary integer programming problems with the min-max regret objective function under interval objective coefficients. We propose a new heuristic framework, which we call the iterated dual substitution (iDS) algorithm. The iDS…

Optimization and Control · Mathematics 2020-12-15 Wei Wu , Manuel Iori , Silvano Martello , Mutsunori Yagiura

This paper studies some basic problems in a multiple-object auction model using methodologies from theoretical computer science. We are especially concerned with situations where an adversary bidder knows the bidding algorithms of all the…

Computational Engineering, Finance, and Science · Computer Science 2007-05-23 Ming-Yang Kao , Junfeng Qi , Lei Tan

We consider the product knapsack problem, which is the variant of the classical 0-1 knapsack problem where the objective consists of maximizing the product of the profits of the selected items. These profits are allowed to be positive or…

Optimization and Control · Mathematics 2021-06-29 Ulrich Pferschy , Joachim Schauer , Clemens Thielen

In the online general knapsack problem, an algorithm is presented with an item $x=(s,v)$ of size $s$ and value $v$ and must irrevocably choose to pack such an item into the knapsack or reject it before the next item appears. The goal is to…

Data Structures and Algorithms · Computer Science 2025-04-30 Elisabet Burjons , Matthias Gehnen

We study the problem of maximizing a non-monotone submodular function under multiple knapsack constraints. We propose a simple discrete greedy algorithm to approach this problem, and prove that it yields strong approximation guarantees for…

Machine Learning · Computer Science 2020-02-19 Vanja Doskoč , Tobias Friedrich , Andreas Göbel , Frank Neumann , Aneta Neumann , Francesco Quinzan

Knapsack and Subset Sum are fundamental NP-hard problems in combinatorial optimization. Recently there has been a growing interest in understanding the best possible pseudopolynomial running times for these problems with respect to various…

Data Structures and Algorithms · Computer Science 2021-05-11 Adam Polak , Lars Rohwedder , Karol Węgrzycki
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