Results 31 to 40 of about 33,818 (220)
Hardness of Approximation for Knapsack Problems [PDF]
Theory of Computing Systems, 2014 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Harry Buhrman +2 more
openaire +3 more sources
Approximation Algorithms for Correlated Knapsacks and Non-Martingale Bandits [PDF]
, 2011 In the stochastic knapsack problem, we are given a knapsack of size B, and a set of jobs whose sizes and rewards are drawn from a known probability distribution. However, we know the actual size and reward only when the job completes.
Gupta, Anupam +3 more
core +2 more sources
Topology Knapsack Problem for Geometry Optimization
IEEE AccessThe knapsack problem is a classic NP-hard optimization challenge with wide-ranging applications in computer science, such as resource allocation. While several variants have been developed, including the 0/1, fractional, and multi-dimensional knapsack ...
Hsiao-Hui Li +2 more
doaj +1 more source
Stochastic Vehicle Routing with Recourse [PDF]
, 2012 We study the classic Vehicle Routing Problem in the setting of stochastic optimization with recourse. StochVRP is a two-stage optimization problem, where demand is satisfied using two routes: fixed and recourse.
A. Ak +26 more
core +1 more source
Solving the 0-1 Knapsack Problem by Using Tissue P System With Cell Division
IEEE Access, 2019 Membrane computing is a kind of distributed and parallel computing model inspired by a biological cell mechanism. The maximum parallelism of membrane computing improves the computational efficiency of its computational model.
Lian Ye +3 more
doaj +1 more source
Online Knapsack Problem under Expected Capacity Constraint
, 2017 Online knapsack problem is considered, where items arrive in a sequential fashion that have two attributes; value and weight. Each arriving item has to be accepted or rejected on its arrival irrevocably.
Vaze, Rahul
core +1 more source
Neural Knapsack: A Neural Network Based Solver for the Knapsack Problem
IEEE Access, 2020 This paper introduces a heuristic solver based on neural networks and deep learning for the knapsack problem. The solver is inspired by mechanisms and strategies used by both algorithmic solvers and humans.
Hazem A. A. Nomer +3 more
doaj +1 more source
Truthful Multi-unit Procurements with Budgets [PDF]
, 2014 We study procurement games where each seller supplies multiple units of his item, with a cost per unit known only to him. The buyer can purchase any number of units from each seller, values different combinations of the items differently, and has a ...
A. Archer +8 more
core +2 more sources
Advanced Electronic Materials, EarlyView.Ising machines are emerging as specialized hardware solvers for computationally hard optimization problems. This review examines five major platforms—digital CMOS, analog CMOS, emerging devices, coherent optics, and quantum systems—highlighting physics‐rooted advantages and shared bottlenecks in scalability and connectivity.
Hyunjun Lee, Joon Pyo Kim, Sanghyeon Kim
wiley +1 more source
Terrestrial Cyborg Insects for Real‐Life Applications
Advanced Intelligent Systems, EarlyView.This article reviews the development of terrestrial cyborg insects from their emergence in 1997 to mid‐2025, examining three key aspects: locomotion control methods, associated challenges with proposed solutions, and practical applications. Framing these biohybrid systems as insect‐scale mobile robots, the review provides foundational insights for new ...
Hai Nhan Le +10 more
wiley +1 more source