TY  - BOOK
AU  - Alavi, Amir
AU  - Wang, Gai-Ge
AB  - Computational intelligence is a general term for a class of algorithms designed by nature's wisdom and human intelligence. Computer scientists have proposed many computational intelligence algorithms with heuristic features. These algorithms either mimic the evolutionary processes of the biological world, mimic the physiological structure and bodily functions of the organism,
DO  - 10.3390/books978-3-03921-929-2
ID  - OAPEN ID: 42682
KW  - individual updating strategy
KW  - integrated design
KW  - global optimum
KW  - flexible job shop scheduling problem
KW  - whale optimization algorithm
KW  - EHO
KW  - bat algorithm with multiple strategy coupling (mixBA)
KW  - multi-objective DV-Hop localization algorithm
KW  - optimization
KW  - rock types
KW  - variable neighborhood search
KW  - biology
KW  - average iteration times
KW  - CEC2013 benchmarks
KW  - slicing tree structure
KW  - firefly algorithm (FA)
KW  - benchmark
KW  - single loop
KW  - evolutionary computation
KW  - memetic algorithm
KW  - normal cloud model
KW  - 0-1 knapsack problems
KW  - elite strategy
KW  - diversity maintenance
KW  - material handling path
KW  - artificial bee colony algorithm (ABC)
KW  - urban design
KW  - entropy
KW  - evolutionary algorithms (EAs)
KW  - monarch butterfly optimization
KW  - numerical simulation
KW  - architecture
KW  - set-union knapsack problem
KW  - Wilcoxon test
KW  - convolutional neural network
KW  - global position updating operator
KW  - particle swarm optimization
KW  - computation
KW  - minimum load coloring
KW  - topology structure
KW  - adaptive multi-swarm
KW  - minimum total dominating set
KW  - mutation operation
KW  - shape grammar
KW  - greedy optimization algorithm
KW  - ?-Hilbert space
KW  - genetic algorithm
KW  - large scale optimization
KW  - large-scale optimization
KW  - NSGA-II-DV-Hop
KW  - constrained optimization problems (COPs)
KW  - first-arrival picking
KW  - transfer function
KW  - SPEA 2
KW  - stochastic ranking (SR)
KW  - wireless sensor networks (WSNs)
KW  - acceleration search
KW  - convergence point
KW  - fuzzy c-means
KW  - evolutionary algorithm
KW  - success rates
KW  - Artificial bee colony
KW  - particle swarm optimizer
KW  - random weight
KW  - range detection
KW  - adaptive weight
KW  - large-scale
KW  - automatic identification
KW  - cloud model
KW  - swarm intelligence
KW  - evolutionary multi-objective optimization
KW  - DV-Hop algorithm
KW  - bat algorithm (BA)
KW  - Friedman test
KW  - quantum uncertainty property
KW  - facility layout design
KW  - local search
KW  - deep learning
KW  - Y conditional cloud generator
KW  - benchmark functions
KW  - discrete algorithm
KW  - dispatching rule
KW  - DE algorithm
KW  - nonlinear convergence factor
KW  - energy-efficient job shop scheduling
KW  - t-test
KW  - evolution
KW  - dimension learning
KW  - global optimization
KW  - confidence term
KW  - elephant herding optimization
KW  - moth search algorithm
KW  - evolutionary
L1  - https://mdpi.com/books/pdfview/book/1860
LA  - English
LK  - https://directory.doabooks.org/handle/20.500.12854/47147
PB  - MDPI - Multidisciplinary Digital Publishing Institute
PY  - 2019
SN  - 9783039219285
SN  - 9783039219292
TI  - Evolutionary Computationnull
ER  - 
