On the public citation graph

On the optimization of unimodal functions with the (1+1) evolutionary algorithm

0 signed · 76 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

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

inferredcites →https://doi.org/10.1002/(sici)1099-0526(199703/04)2:4<28::aid-cplx7>3.0.co;2-2openalex-snapshot
Evolutionary computation: Toward a new philosophy of machine intelligence
inferredcites →https://doi.org/10.1007/3-540-58484-6_259openalex-snapshot
Long path problems
inferredcites →https://doi.org/10.1007/3-540-61723-xopenalex-snapshot
Parallel Problem Solving from Nature — PPSN IV
inferredcites →https://doi.org/10.1007/3-540-61723-x_977openalex-snapshot
Are long path problems hard for genetic algorithms?
inferredcites →https://doi.org/10.1109/4235.585893openalex-snapshot
No free lunch theorems for optimization
inferredcites →https://doi.org/10.1109/icec.1998.700079openalex-snapshot
A rigorous complexity analysis of the (1+1) evolutionary algorithm for linear functions with Boolean inputs
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/10.5860/choice.27-0936openalex-snapshot
Genetic algorithms in search, optimization, and machine learning
inferredcites →https://doi.org/10.7551/mitpress/1090.001.0001openalex-snapshot
Adaptation in Natural and Artificial Systems

What points at this work

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

inferred← citeshttps://doi.org/10.1002/wics.70028openalex-snapshot
A Review of Benchmark and Test Functions for Global Optimization Algorithms and Metaheuristics
inferred← citeshttps://doi.org/10.1007/0-306-48041-7_14openalex-snapshot
Methods for the Analysis of Evolutionary Algorithms on Pseudo-Boolean Functions
inferred← citeshttps://doi.org/10.1007/11513575_7openalex-snapshot
Running Time Analysis of a Multiobjective Evolutionary Algorithm on Simple and Hard Problems
inferred← citeshttps://doi.org/10.1007/3-540-36494-3_37openalex-snapshot
Evolutionary Algorithms and the Maximum Matching Problem
inferred← citeshttps://doi.org/10.1007/3-540-45712-7_6openalex-snapshot
Fitness Landscapes Based on Sorting and Shortest Paths Problems
inferred← citeshttps://doi.org/10.1007/3-540-48224-5_6openalex-snapshot
Theoretical Aspects of Evolutionary Algorithms
inferred← citeshttps://doi.org/10.1007/978-3-030-58115-2_43openalex-snapshot
Exponential Upper Bounds for the Runtime of Randomized Search Heuristics
inferred← citeshttps://doi.org/10.1007/978-3-030-58115-2_48openalex-snapshot
Approximation Speed-Up by Quadratization on LeadingOnes
inferred← citeshttps://doi.org/10.1007/978-3-319-11683-9_5openalex-snapshot
Linear Convergence of Evolution Strategies with Derandomized Sampling Beyond Quasi-Convex Functions
inferred← citeshttps://doi.org/10.1007/978-3-540-30499-9_28openalex-snapshot
Expected Running Time Analysis of a Multiobjective Evolutionary Algorithm on Pseudo-boolean Functions
inferred← citeshttps://doi.org/10.1007/978-3-642-15844-5_5openalex-snapshot
Optimizing Monotone Functions Can Be Difficult
inferred← citeshttps://doi.org/10.1007/978-3-642-17339-4_5openalex-snapshot
Methods for the Analysis of Evolutionary Algorithms
inferred← citeshttps://doi.org/10.1007/978-3-642-25566-3_3openalex-snapshot
On the Effect of Connectedness for Biobjective Multiple and Long Path Problems
inferred← citeshttps://doi.org/10.1007/978-3-642-38416-5_9openalex-snapshot
Theoretical Advances in Evolutionary Dynamic Optimization
inferred← citeshttps://doi.org/10.1007/978-3-662-04448-3_18openalex-snapshot
On Classifications of Fitness Functions
inferred← citeshttps://doi.org/10.1007/978-3-662-04448-3_6openalex-snapshot
Theory of Evolution Strategies — A Tutorial
inferred← citeshttps://doi.org/10.1007/978-3-662-05609-7_5openalex-snapshot
Theory of Evolutionary Algorithms and Genetic Programming
inferred← citeshttps://doi.org/10.1007/s00453-009-9352-xopenalex-snapshot
Precision, Local Search and Unimodal Functions
inferred← citeshttps://doi.org/10.1007/s10664-020-09937-1openalex-snapshot
Resource and dependency based test case generation for RESTful Web services
inferred← citeshttps://doi.org/10.1007/s10852-005-2584-0openalex-snapshot
The analysis of evolutionary algorithms on sorting and shortest paths problems
inferred← citeshttps://doi.org/10.1007/s10915-022-01955-zopenalex-snapshot
Robust Grey Wolf Optimizer for Multimodal Optimizations: A Cross-Dimensional Coordination Approach
inferred← citeshttps://doi.org/10.1007/s11633-007-0281-3openalex-snapshot
Time complexity of evolutionary algorithms for combinatorial optimization: A decade of results
inferred← citeshttps://doi.org/10.1007/s11704-009-0006-6openalex-snapshot
Runtime analysis of search heuristics on software engineering problems
inferred← citeshttps://doi.org/10.1016/j.artint.2008.07.001openalex-snapshot
A new approach to estimating the expected first hitting time of evolutionary algorithms
inferred← citeshttps://doi.org/10.1016/j.jda.2005.01.002openalex-snapshot
On the analysis of a dynamic evolutionary algorithm
inferred← citeshttps://doi.org/10.1016/j.tcs.2006.03.007openalex-snapshot
Analysis of a Multiobjective Evolutionary Algorithm on the 0–1 knapsack problem
inferred← citeshttps://doi.org/10.1016/s0304-3975(02)00137-8openalex-snapshot
How to analyse evolutionary algorithms
inferred← citeshttps://doi.org/10.1017/cbo9780511852008.014openalex-snapshot
Pseudo-Boolean functions
inferred← citeshttps://doi.org/10.1023/a:1015059928466openalex-snapshot
Evolution strategies – A comprehensive introduction
inferred← citeshttps://doi.org/10.1109/4235.974841openalex-snapshot
Evolutionary algorithms - how to cope with plateaus of constant fitness and when to reject strings of the same fitness
inferred← citeshttps://doi.org/10.1109/cec.1999.782521openalex-snapshot
Applying evolutionary algorithms to real-world-inspired problems with physical smoothness constraints
inferred← citeshttps://doi.org/10.1109/cec.2003.1299908openalex-snapshot
Expected runtimes of a simple multi-objective evolutionary algorithm
inferred← citeshttps://doi.org/10.1109/cec.2004.1330959openalex-snapshot
The curse of high-dimensional search spaces: observing premature convergence in unimodal functions
inferred← citeshttps://doi.org/10.1109/cec.2007.4424701openalex-snapshot
Evolutionary algorithms and the Vertex Cover problem
inferred← citeshttps://doi.org/10.1109/cec.2013.6557756openalex-snapshot
A (1+1) Adaptive Memetic Algorithm for the Maximum Clique Problem
inferred← citeshttps://doi.org/10.1109/iecon.2000.972425openalex-snapshot
A natural and simple function which is hard for all evolutionary algorithms
inferred← citeshttps://doi.org/10.1109/tevc.2006.888929openalex-snapshot
A Runtime Analysis of Evolutionary Algorithms for Constrained Optimization Problems
inferred← citeshttps://doi.org/10.1109/tevc.2009.2014362openalex-snapshot
Analysis of the $(1+1)$-EA for Finding Approximate Solutions to Vertex Cover Problems
inferred← citeshttps://doi.org/10.1109/tsmcb.2008.2012167openalex-snapshot
A New Approach for Analyzing Average Time Complexity of Population-Based Evolutionary Algorithms on Unimodal Problems
inferred← citeshttps://doi.org/10.1142/9789814282673_0002openalex-snapshot
Runtime Analysis of Evolutionary Algorithms for Discrete Optimization
inferred← citeshttps://doi.org/10.1145/1389095.1389249openalex-snapshot
Precision, local search and unimodal functions
inferred← citeshttps://doi.org/10.1145/1389095.1389274openalex-snapshot
Comparing global and local mutations on bit strings
inferred← citeshttps://doi.org/10.1145/3377929.3389889openalex-snapshot
A gentle introduction to theory (for non-theoreticians)
inferred← citeshttps://doi.org/10.1145/3377930.3390144openalex-snapshot
Understanding transforms of pseudo-boolean functions
inferred← citeshttps://doi.org/10.1145/3449639.3459398openalex-snapshot
Non-elitist evolutionary algorithms excel in fitness landscapes with sparse deceptive regions and dense valleys
inferred← citeshttps://doi.org/10.1145/3449726.3461406openalex-snapshot
A gentle introduction to theory (for non-theoreticians)
inferred← citeshttps://doi.org/10.1145/3520304.3533628openalex-snapshot
A gentle introduction to theory (for non-theoreticians)
inferred← citeshttps://doi.org/10.1145/3583133.3595042openalex-snapshot
A Gentle Introduction to Theory (for Non-Theoreticians)
inferred← citeshttps://doi.org/10.1145/3638530.3648402openalex-snapshot
A Gentle Introduction to Theory (for Non-Theoreticians)
inferred← citeshttps://doi.org/10.1145/3712255.3716526openalex-snapshot
Tutorial: A Gentle Introduction to Theory (for Non-Theoreticians)
inferred← citeshttps://doi.org/10.1162/1063656043138905openalex-snapshot
The Cooperative Coevolutionary (1+1) EA
inferred← citeshttps://doi.org/10.1162/106365605774666921openalex-snapshot
On the Choice of the Offspring Population Size in Evolutionary Algorithms
inferred← citeshttps://doi.org/10.1162/evco_a_00055openalex-snapshot
Mutation Rate Matters Even When Optimizing Monotonic Functions
inferred← citeshttps://doi.org/10.1162/evco_a_00119openalex-snapshot
Parameterized Runtime Analyses of Evolutionary Algorithms for the Planar Euclidean Traveling Salesperson Problem
inferred← citeshttps://doi.org/10.1609/aaai.v26i1.8273openalex-snapshot
A Parameterized Runtime Analysis of Evolutionary Algorithms for the Euclidean Traveling Salesperson Problem
inferred← citeshttps://doi.org/10.17877/de290r-1190openalex-snapshot
Theoretische Analyse evolutionärer Algorithmen unter dem Aspekt der Optimierung in diskreten Suchräumen
inferred← citeshttps://doi.org/10.17877/de290r-14196openalex-snapshot
A New Framework for the Valuation of Algorithms for Black-Box-Optimization
inferred← citeshttps://doi.org/10.17877/de290r-15351openalex-snapshot
On the design and analysis of evolutionary algorithms
inferred← citeshttps://doi.org/10.17877/de290r-15362openalex-snapshot
Searching Randomly for Maximum Matchings
inferred← citeshttps://doi.org/10.17877/de290r-2062openalex-snapshot
Theoretical foundations of artificial immune systems
inferred← citeshttps://doi.org/10.2307/jj.1895841.5openalex-snapshot
A Comprehensive Introduction
inferred← citeshttps://doi.org/10.2478/v10006-012-0072-zopenalex-snapshot
The island model as a Markov dynamic system
inferred← citeshttps://doi.org/10.25916/sut.26275387openalex-snapshot
Optimizing and matching bitstrings
inferred← citeshttps://doi.org/10.48550/arxiv.1010.1429openalex-snapshot
Optimizing Monotone Functions Can Be Difficult
inferred← citeshttps://doi.org/10.48550/arxiv.1207.0578openalex-snapshot
Parameterized Runtime Analyses of Evolutionary Algorithms for the Euclidean Traveling Salesperson Problem
inferred← citeshttps://doi.org/10.48550/arxiv.1807.02754openalex-snapshot
Model-Free Optimization Using Eagle Perching Optimizer
inferred← citeshttps://doi.org/10.70675/40b6ab5az6c45z4e4az8ef4z7853ec7a70ddopenalex-snapshot
Hybridization of dynamic optimization methodologies
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.