Memetic algorithms for the unconstrained binary quadratic programming problem
P Merz, K Katayama - BioSystems, 2004 - Elsevier
This paper presents a memetic algorithm, a highly effective evolutionary algorithm
incorporating local search for solving the unconstrained binary quadratic programming …
incorporating local search for solving the unconstrained binary quadratic programming …
On metaheuristic algorithms for combinatorial optimization problems
M Yagiura, T Ibaraki - Systems and Computers in Japan, 2001 - Wiley Online Library
Metaheuristic algorithms are widely recognized as one of the most practical approaches for
combinatorial optimization problems. Among representative metaheuristics are genetic …
combinatorial optimization problems. Among representative metaheuristics are genetic …
Population evolvability: Dynamic fitness landscape analysis for population-based metaheuristic algorithms
Fitness landscape analysis (FLA) is an important approach for studying how hard problems
are for metaheuristic algorithms to solve. Static FLA focuses on extracting the properties of a …
are for metaheuristic algorithms to solve. Static FLA focuses on extracting the properties of a …
[图书][B] Ant colony optimization and constraint programming
C Solnon - 2010 - Wiley Online Library
The ability of ant colonies to form paths for carrying food is rather fascinating. When
considering the scale of ants, this path-finding problem is complex: ants only have a local …
considering the scale of ants, this path-finding problem is complex: ants only have a local …
Empirical analysis of locality, heritability and heuristic bias in evolutionary algorithms: A case study for the multidimensional knapsack problem
GR Raidl, J Gottlieb - Evolutionary computation, 2005 - ieeexplore.ieee.org
Our main aim is to provide guidelines and practical help for the design of appropriate
representations and operators for evolutionary algorithms (EAs). For this purpose, we …
representations and operators for evolutionary algorithms (EAs). For this purpose, we …
Automatic path planning of unmanned combat aerial vehicle based on double-layer coding method with enhanced grey wolf optimizer
Y Jia, L Qu, X Li - Artificial Intelligence Review, 2023 - Springer
The unmanned combat aerial vehicle (UCAV) technology has to deal with a lot of challenges
in complex battlefield environments. The UCAV requires a high number of points to build the …
in complex battlefield environments. The UCAV requires a high number of points to build the …
Fitness landscape analysis of automated machine learning search spaces
Abstract The field of Automated Machine Learning (AutoML) has as its main goal to
automate the process of creating complete Machine Learning (ML) pipelines to any dataset …
automate the process of creating complete Machine Learning (ML) pipelines to any dataset …
A study of ACO capabilities for solving the maximum clique problem
This paper investigates the capabilities of the Ant Colony Optimization (ACO) meta-heuristic
for solving the maximum clique problem, the goal of which is to find a largest set of pairwise …
for solving the maximum clique problem, the goal of which is to find a largest set of pairwise …
A meta-learning prediction model of algorithm performance for continuous optimization problems
Algorithm selection and configuration is a challenging problem in the continuous
optimization domain. An approach to tackle this problem is to develop a model that links …
optimization domain. An approach to tackle this problem is to develop a model that links …
Adaptive recommendation model using meta-learning for population-based algorithms
To efficiently solve complex optimization problems, numerous population-based meta-
heuristics and extensions have been developed. However, the performances of the …
heuristics and extensions have been developed. However, the performances of the …