`` Direct Search'' Solution of Numerical and Statistical Problems
Journal of the ACM (JACM)
Multimeme Algorithms for Protein Structure Prediction
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
A Hyperheuristic Approach to Scheduling a Sales Summit
PATAT '00 Selected papers from the Third International Conference on Practice and Theory of Automated Timetabling III
A Tabu-Search Hyperheuristic for Timetabling and Rostering
Journal of Heuristics
Advanced fitness landscape analysis and the performance of memetic algorithms
Evolutionary Computation - Special issue on magnetic algorithms
Evolutionary Computation - Special issue on magnetic algorithms
Soft Computing - A Fusion of Foundations, Methodologies and Applications
An Adaptive Multimeme Algorithm for Designing HIV Multidrug Therapies
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
A memetic algorithm and a tabu search for the multi-compartment vehicle routing problem
Computers and Operations Research
An enhanced memetic differential evolution in filter design for defect detection in paper production
Evolutionary Computation
Super-fit control adaptation in memetic differential evolution frameworks
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special Issue on Emerging Trends in Soft Computing - Memetic Algorithms; Guest Editors: Yew-Soon Ong, Meng-Hiot Lim, Ferrante Neri, Hisao Ishibuchi
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Two memetic algorithms for heterogeneous fleet vehicle routing problems
Engineering Applications of Artificial Intelligence
Differential evolution algorithm with strategy adaptation for global numerical optimization
IEEE Transactions on Evolutionary Computation
A probabilistic memetic framework
IEEE Transactions on Evolutionary Computation
Recent advances in differential evolution: a survey and experimental analysis
Artificial Intelligence Review
JADE: adaptive differential evolution with optional external archive
IEEE Transactions on Evolutionary Computation
Frankenstein's PSO: a composite particle swarm optimization algorithm
IEEE Transactions on Evolutionary Computation
Memetic algorithms for continuous optimisation based on local search chains
Evolutionary Computation
Ensemble of niching algorithms
Information Sciences: an International Journal
Research frontier: memetic computation-past, present & future
IEEE Computational Intelligence Magazine
Benefits of a population: five mechanisms that advantage population-based algorithms
IEEE Transactions on Evolutionary Computation
Disturbed Exploitation compact Differential Evolution for limited memory optimization problems
Information Sciences: an International Journal
Handbook of Memetic Algorithms
Handbook of Memetic Algorithms
Ockham's Razor in memetic computing: Three stage optimal memetic exploration
Information Sciences: an International Journal
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special Issue on scalability of evolutionary algorithms and other metaheuristics for large-scale continuous optimization problems
The differential ant-stigmergy algorithm
Information Sciences: an International Journal
Estimation of particle swarm distribution algorithms: Combining the benefits of PSO and EDAs
Information Sciences: an International Journal
No free lunch theorems for optimization
IEEE Transactions on Evolutionary Computation
Meta-Lamarckian learning in memetic algorithms
IEEE Transactions on Evolutionary Computation
A tutorial for competent memetic algorithms: model, taxonomy, and design issues
IEEE Transactions on Evolutionary Computation
Comprehensive learning particle swarm optimizer for global optimization of multimodal functions
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Evolutionary Computation
Classification of adaptive memetic algorithms: a comparative study
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A Fast Adaptive Memetic Algorithm for Online and Offline Control Design of PMSM Drives
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Coevolving Memetic Algorithms: A Review and Progress Report
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A Memetic Algorithm for Multiple-Drug Cancer Chemotherapy Schedule Optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Estimating meme fitness in adaptive memetic algorithms for combinatorial problems
Evolutionary Computation
A Multi-Facet Survey on Memetic Computation
IEEE Transactions on Evolutionary Computation
A framework for evolutionary algorithms based on Charles Sanders Peirce's evolutionary semiotics
Information Sciences: an International Journal
Adaptive Memetic Differential Evolution with Global and Local neighborhood-based mutation operators
Information Sciences: an International Journal
Region based memetic algorithm for real-parameter optimisation
Information Sciences: an International Journal
An analysis on separability for Memetic Computing automatic design
Information Sciences: an International Journal
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Memetic Computing (MC) structures are algorithms composed of heterogeneous operators (memes) for solving optimization problems. In order to address these problems, this study investigates and proposes a simple yet extremely efficient structure, namely Parallel Memetic Structure (PMS). PMS is a single solution optimization algorithm composed of tree operators, the first one being a stochastic global search which explores the entire decision space searching for promising regions. In analogy with electrical networks, downstream of the global search component there is a parallel of two alternative elements, i.e. two local search algorithms with different features in terms of search logic, whose purpose is to refine the search in the regions detected by the upstream element. The first local search explores the space along the axes, while the second performs diagonal movements in the direction of the estimated gradient. The PMS algorithm, despite its simplicity, displays a respectable performance compared to that of popular meta-heuristics and modern optimization algorithms representing the state-of-the-art in the field. Thanks to its simple structure, PMS appears to be a very flexible algorithm for various problem features and dimensionality values. Unlike modern complex algorithm that are specialized for some benchmarks and some dimensionality values, PMS achieves solutions with a high quality in various and diverse contexts, for example both on low dimensional and large scale problems. An application example in the field of magnetic sensors further proves the potentials of the proposed approach. This study confirms the validity of the Ockham's Razor in MC: efficiently designed simple structures can perform as well as (if not better than) complex algorithms composed of many parts.