ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1404.3520
  4. Cited By
A Theoretical Assessment of Solution Quality in Evolutionary Algorithms
  for the Knapsack Problem

A Theoretical Assessment of Solution Quality in Evolutionary Algorithms for the Knapsack Problem

14 April 2014
Jun He
B. Mitavskiy
Yuren Zhou
ArXivPDFHTML

Papers citing "A Theoretical Assessment of Solution Quality in Evolutionary Algorithms for the Knapsack Problem"

4 / 4 papers shown
Title
Runtime Performance of Evolutionary Algorithms for the Chance-constrained Makespan Scheduling Problem
Runtime Performance of Evolutionary Algorithms for the Chance-constrained Makespan Scheduling Problem
Feng Shi
Xiankun Yan
Frank Neumann
Frank Neumann
118
0
0
22 Dec 2022
Performance Analysis on Evolutionary Algorithms for the Minimum Label
  Spanning Tree Problem
Performance Analysis on Evolutionary Algorithms for the Minimum Label Spanning Tree Problem
Xinsheng Lai
Yuren Zhou
Jun He
Jun Zhang
75
36
0
03 Sep 2014
A Novel Genetic Algorithm using Helper Objectives for the 0-1 Knapsack
  Problem
A Novel Genetic Algorithm using Helper Objectives for the 0-1 Knapsack Problem
Jun He
Feidun He
Hongbin Dong
140
2
0
03 Apr 2014
Mixed Strategy May Outperform Pure Strategy: An Initial Study
Mixed Strategy May Outperform Pure Strategy: An Initial Study
Jun He
Wei-gen Hou
Hongbin Dong
Feidun He
43
11
0
13 Mar 2013
1