Evolutionary Computation & Swarm Intelligence (MDPI - Multidisciplinary Digital Publishing Institute, 2020)
Keywords: algorithmic design; analysis; approximate matching; benchmark suite; compact optimization; concept drift; concept evolution; context-triggered piecewise hashing; data integration; data sampling; DE-MPFSC algorithm; density based clustering; derivative-free; discrete optimization; dynamic stream clustering; Economics, Finance, Business and Management; edit distance; entanglement degree; estimation distribution algorithms; evolutionary algorithms; evolutionary computation; feature selection; fitness trend; fuzzy hashing; genetic algorithm; global/local optimization; Holm–Bonferroni; hybrid algorithms; identification; imbalanced data; Industry and industrial studies; Information technology industries; instance weighting; k-means centroid; kinematic parameters; large-scale optimization; LZJD; manipulator; Markov process; maximum k-coverage; Media, entertainment, information and communication industries; memetic algorithms; memetic computing; meta-heuristic algorithms; metaheuristic optimisation; metaheuristics; multi-objective deterministic optimization; multi-thread programming; nature-inspired algorithms; normalization; one billion variables; online clustering; optimisation; parameter tuning; particle swarm; Particle Swarm Optimization; population based algorithms; PSO; redundant representation; robot; routing; screening criteria; sdhash; signatures; similarity detection; simulation-based design optimization; Social Network Optimization; ssdeep; Swarm Intelligence; Wilcoxon rank-sum; wireless sensor networks