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Running Time Analysis of a Multiobjective Evolutionary Algorithm on Simple and Hard Problems

https://doi.org/10.1007/11513575_7
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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High Performance Computing - HiPC 2006
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On observing nondeterminism and concurrency
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Convergence Time Analysis for the Multi-objective Counting Ones Problem
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Analysis of a Simple Evolutionary Algorithm for Minimization in Euclidean Spaces
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Genetic and Evolutionary Computation — GECCO 2003
inferredcites →https://doi.org/10.1007/3-540-45110-2_113openalex-snapshot
Multicriteria Network Design Using Evolutionary Algorithm
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Parallel Problem Solving from Nature PPSN VI
inferredcites →https://doi.org/10.1007/3-540-45356-3_83openalex-snapshot
A Fast Elitist Non-dominated Sorting Genetic Algorithm for Multi-objective Optimization: NSGA-II
inferredcites →https://doi.org/10.1007/3-540-45712-7openalex-snapshot
Parallel Problem Solving from Nature — PPSN VII
inferredcites →https://doi.org/10.1007/3-540-45712-7_5openalex-snapshot
Running Time Analysis of Multi-objective Evolutionary Algorithms on a Simple Discrete Optimization Problem
inferredcites →https://doi.org/10.1007/3-540-45712-7_6openalex-snapshot
Fitness Landscapes Based on Sorting and Shortest Paths Problems
inferredcites →https://doi.org/10.1007/978-0-387-36797-2openalex-snapshot
Evolutionary Algorithms for Solving Multi-Objective Problems
inferredcites →https://doi.org/10.1007/978-1-4757-5184-0openalex-snapshot
Evolutionary Algorithms for Solving Multi-Objective Problems
inferredcites →https://doi.org/10.1007/978-3-540-30474-6_52openalex-snapshot
Improved Quality of Solutions for Multiobjective Spanning Tree Problem Using Distributed Evolutionary Algorithm
inferredcites →https://doi.org/10.1007/bfb0040787openalex-snapshot
Evolutionary search for minimal elements in partially ordered finite sets
inferredcites →https://doi.org/10.1007/bfb0056843openalex-snapshot
Parallel Problem Solving from Nature — PPSN V
inferredcites →https://doi.org/10.1007/bfb0056845openalex-snapshot
On the optimization of unimodal functions with the (1+1) evolutionary algorithm
inferredcites →https://doi.org/10.1007/s00453-002-0940-2openalex-snapshot
The Analysis of Evolutionary Algorithms—A Proof That Crossover Really Can Help
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Approximation algorithms for the m-dimensional 0–1 knapsack problem: Worst-case and probabilistic analyses
inferredcites →https://doi.org/10.1016/j.jda.2004.02.001openalex-snapshot
On the analysis of a simple evolutionary algorithm on quadratic pseudo-boolean functions
inferredcites →https://doi.org/10.1016/s0304-3975(01)00182-7openalex-snapshot
On the analysis of the (1+1) evolutionary algorithm
inferredcites →https://doi.org/10.1016/s0304-3975(02)00137-8openalex-snapshot
How to analyse evolutionary algorithms
inferredcites →https://doi.org/10.1023/b:naco.0000023415.22052.55openalex-snapshot
Running time analysis of evolutionary algorithms on a simplified multiobjective knapsack problem
inferredcites →https://doi.org/10.1109/4235.797969openalex-snapshot
Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach
inferredcites →https://doi.org/10.1109/4235.996017openalex-snapshot
A fast and elitist multiobjective genetic algorithm: NSGA-II
inferredcites →https://doi.org/10.1109/72.712155openalex-snapshot
Multiobjective genetic algorithm partitioning for hierarchical learning of high-dimensional pattern spaces: a learning-follows-decomposition strategy
inferredcites →https://doi.org/10.1109/cec.2000.870756openalex-snapshot
Convergence properties of some multi-objective evolutionary algorithms
inferredcites →https://doi.org/10.1109/cec.2001.934439openalex-snapshot
A comparison of encodings and algorithms for multiobjective minimum spanning tree problems
inferredcites →https://doi.org/10.1109/cec.2002.1006272openalex-snapshot
Topological design of communication networks using multiobjective genetic optimization
inferredcites →https://doi.org/10.1109/tevc.2003.810758openalex-snapshot
Performance assessment of multiobjective optimizers: an analysis and review
inferredcites →https://doi.org/10.1109/tevc.2004.823470openalex-snapshot
Running Time Analysis of Multiobjective Evolutionary Algorithms on Pseudo-Boolean Functions
inferredcites →https://doi.org/10.1145/1830761.1830909openalex-snapshot
Evolutionary multi-criterion optimization
inferredcites →https://doi.org/10.1145/261342.571216openalex-snapshot
Approximation Algorithms for NP-Hard Problems
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Book review: Approximation Algorithms for NP-hard Problems. Edited by Dorit S. Hochbaum (PWS, 1997)
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Fast Approximation Algorithms for the Knapsack and Sum of Subset Problems
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Approximating the Nondominated Front Using the Pareto Archived Evolution Strategy
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Improved Sampling of the Pareto-Front in Multiobjective Genetic Optimizations by Steady-State Evolution: A Pareto Converging Genetic Algorithm
inferredcites →https://doi.org/10.1162/evco.1996.4.2.195openalex-snapshot
How Mutation and Selection Solve Long-Path Problems in Polynomial Expected Time
inferredcites →https://doi.org/10.1162/evco.1999.7.2.173openalex-snapshot
Rigorous Hitting Times for Binary Mutations
inferredcites →https://doi.org/10.1287/mnsc.48.12.1603.445openalex-snapshot
Approximating Multiobjective Knapsack Problems
inferredcites →https://doi.org/10.17877/de290r-14196openalex-snapshot
A New Framework for the Valuation of Algorithms for Black-Box-Optimization
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SPEA2: Improving the strength pareto evolutionary algorithm

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4837969openalex-extracted
Runtime Performance of Evolutionary Algorithms for the Chanceconstrained Makespan Scheduling Problem
inferred← citeshttps://doi.org/10.1007/978-1-4020-6264-3_75openalex-snapshot
Bond Graph Causality Assignment and Evolutionary Multi-Objective Optimization
inferred← citeshttps://doi.org/10.1007/978-3-319-99259-4_12openalex-snapshot
Runtime Analysis of Evolutionary Algorithms for the Knapsack Problem with Favorably Correlated Weights
inferred← citeshttps://doi.org/10.1007/978-3-540-36266-1_32openalex-snapshot
Evolutionary and Heuristic Algorithms for Multiobjective 0–1 Knapsack Problem
inferred← citeshttps://doi.org/10.1007/978-3-642-13278-0_21openalex-snapshot
A Quantum-Inspired Artificial Immune System for Multiobjective 0-1 Knapsack Problems
inferred← citeshttps://doi.org/10.1007/978-3-642-15844-5_61openalex-snapshot
Tight Bounds for the Approximation Ratio of the Hypervolume Indicator
inferred← citeshttps://doi.org/10.1007/s10489-008-0148-5openalex-snapshot
MulRoGA: A Multicast Routing Genetic Algorithm approach considering multiple objectives
inferred← citeshttps://doi.org/10.1007/s11042-020-09399-zopenalex-snapshot
Analysis of multiobjective evolutionary algorithms on the biobjective traveling salesman problem (1,2)
inferred← citeshttps://doi.org/10.1016/j.artint.2012.09.005openalex-snapshot
Approximation quality of the hypervolume indicator
inferred← citeshttps://doi.org/10.1016/j.asoc.2009.08.037openalex-snapshot
Assessing solution quality of biobjective 0-1 knapsack problem using evolutionary and heuristic algorithms
inferred← citeshttps://doi.org/10.1016/j.ejor.2007.04.007openalex-snapshot
An empirical study on similarity-based mating for evolutionary multiobjective combinatorial optimization
inferred← citeshttps://doi.org/10.1016/j.ins.2017.09.066openalex-snapshot
Multi-Objective Simultaneous Optimistic Optimization
inferred← citeshttps://doi.org/10.1016/j.tcs.2021.09.003openalex-snapshot
Time complexity analysis of evolutionary algorithms for 2-hop (1,2)-minimum spanning tree problem
inferred← citeshttps://doi.org/10.1109/cec.2006.1688621openalex-snapshot
Multiobjective Genetic Algorithm for Multicast Routing
inferred← citeshttps://doi.org/10.1145/1143997.1144126openalex-snapshot
Incorporation of decision maker's preference into evolutionary multiobjective optimization algorithms
inferred← citeshttps://doi.org/10.1145/1389095.1389335openalex-snapshot
Evolution of hyperheuristics for the biobjective 0/1 knapsack problem by multiobjective genetic programming
inferred← citeshttps://doi.org/10.1145/1830483.1830576openalex-snapshot
The maximum hypervolume set yields near-optimal approximation
inferred← citeshttps://doi.org/10.1145/1967654.1967662openalex-snapshot
The logarithmic hypervolume indicator
inferred← citeshttps://doi.org/10.1145/3299904.3340315openalex-snapshot
Runtime analysis of the (1 + 1) evolutionary algorithm for the chance-constrained knapsack problem
inferred← citeshttps://doi.org/10.32657/10356/70300openalex-snapshot
Multi-scale search for black-box optimization : theory & algorithms
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