Skip to search formSkip to main content
You are currently offline. Some features of the site may not work correctly.

Optimization problem

Known as: NP optimization problem, Optimal solution, Optimal value 
In mathematics and computer science, an optimization problem is the problem of finding the best solution from all feasible solutions. Optimization… Expand
Wikipedia

Related topics

Related topics

50 relations
APXApproximation-preserving reductionBOBYQABackpropagation
Expand

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Review
2019
Review
2019
A survey of adjustable robust optimization
Static robust optimization (RO) is a methodology to solve mathematical optimization problems with uncertain data. The objective… Expand
Review
2019
Review
2019
Electric, hybrid, and turboelectric fixed-wing aircraft: A review of concepts, models, and design approaches
Abstract Following high-profile government and industry studies, electric aircraft propulsion has emerged as an important… Expand
  • figure 1
  • figure 2
  • table 3
  • figure 3
  • figure 4
Review
2019
Review
2019
Review of numerical optimization techniques for meta-device design [Invited]
Optimization techniques have been indispensable for designing high-performance meta-devices targeted to a wide range of… Expand
  • figure 1
  • figure 2
  • figure 4
  • figure 5
  • figure 6
Review
2019
Review
2019
Ensemble strategies for population-based optimization algorithms - A survey
Abstract In population-based optimization algorithms (POAs), given an optimization problem, the quality of the solutions depends… Expand
Review
2019
Review
2019
A unified framework for stochastic optimization
  • W. Powell
  • Eur. J. Oper. Res.
  • 2019
    • Corpus ID: 85512222
Abstract Stochastic optimization is an umbrella term that includes over a dozen fragmented communities, using a patchwork of… Expand
  • figure 1
  • figure 2
  • figure 3
  • table 1
Review
2019
Review
2019
You Only Propagate Once: Painless Adversarial Training Using Maximal Principle
Deep learning achieves state-of-the-art results in many areas. However recent works have shown that deep networks can be… Expand
  • figure 1
  • figure 2
  • table 1
  • table 2
  • table 3
Review
2019
Review
2019
Data-Driven Evolutionary Optimization: An Overview and Case Studies
Most evolutionary optimization algorithms assume that the evaluation of the objective and constraint functions is straightforward… Expand
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • table 1
Review
2019
Review
2019
Cellular-Enabled UAV Communication: A Connectivity-Constrained Trajectory Optimization Perspective
Integrating the unmanned aerial vehicles (UAVs) into the cellular network is envisioned to be a promising technology to… Expand
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • figure 5
Review
2018
Review
2018
A Survey of Collaborative Filtering-Based Recommender Systems: From Traditional Methods to Hybrid Methods Based on Social Networks
In the era of big data, recommender system (RS) has become an effective information filtering tool that alleviates information… Expand
  • figure 2
  • figure 1
  • table I
  • figure 3
  • figure 5
Review
2018
Review
2018
Bayesian network based extreme learning machine for subjectivity detection
Abstract Subjectivity detection is a task of natural language processing that aims to remove ‘factual’ or ‘neutral’ content, i.e… Expand
By clicking accept or continuing to use the site, you agree to the terms outlined in our Privacy Policy, Terms of Service, and Dataset License
ACCEPT & CONTINUE