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This book was established after the 6th International Workshop on Numerical and Evolutionary Optimization (NEO), representing a collection of papers on the intersection of the two research areas covered at this workshop: numerical optimization and evolutionary search techniques. While focusing on the design of fast and reliable methods lying across these two paradigms, the resulting techniques are strongly applicable to a broad class of realworld problems, such as pattern recognition, routing, energy, lines of production, prediction, and modeling, among others. This volume is intended to serve as a useful reference for mathematicians, engineers, and computer scientists to explore current issues and solutions emerging from these mathematical and computational methods and their applications.
genetic programming  driving scoring functions  driving events  risky driving  intelligent transportation systems  mixture experiments  single component constraints  genetic algorithm  IVoptimality criterion  multiobjective optimization  optimal control  model order reduction  model predictive control  location routing problem  rubber  modify differential evolution algorithm  vehicle routing problem  differential evolution algorithm  crop planning  economic crops  improvement differential evolution algorithm  averaged Hausdorff distance  evolutionary multiobjective optimization  power means  metric measure spaces  performance indicator  Pareto front  surrogatebased optimization  numerical simulations  shape morphing  bulbous bow  opensource framework  Ushaped assembly line balancing  basic differential evolution algorithm  improved differential evolution algorithm  optimal solutions  Genetic Programming  Bloat  NEAT  Local Search  EvoSpace  improved differential evolution algorithm  flexible job shop scheduling problem  local search and jump search  evolutionary computation  multiobjective optimization  decision space diversity
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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,
artificial bee colony algorithm (ABC)  cloud model  normal cloud model  Y conditional cloud generator  global optimum  evolution  computation  urban design  biology  shape grammar  architecture  SPEA 2  energyefficient job shop scheduling  dispatching rule  nonlinear convergence factor  mutation operation  whale optimization algorithm  particle swarm optimization  confidence term  random weight  benchmark functions  ttest  success rates  average iteration times  setunion knapsack problem  moth search algorithm  transfer function  discrete algorithm  evolutionary multiobjective optimization  convergence point  acceleration search  evolutionary computation  optimization  bat algorithm (BA)  bat algorithm with multiple strategy coupling (mixBA)  CEC2013 benchmarks  Wilcoxon test  Friedman test  facility layout design  single loop  monarch butterfly optimization  slicing tree structure  material handling path  integrated design  wireless sensor networks (WSNs)  DVHop algorithm  multiobjective DVHop localization algorithm  NSGAIIDVHop  firstarrival picking  fuzzy cmeans  particle swarm optimization  range detection  minimum total dominating set  evolutionary algorithm  genetic algorithm  local search  constrained optimization problems (COPs)  evolutionary algorithms (EAs)  firefly algorithm (FA)  stochastic ranking (SR)  Artificial bee colony  swarm intelligence  elite strategy  dimension learning  global optimization  DE algorithm  ?Hilbert space  topology structure  quantum uncertainty property  numerical simulation  whale optimization algorithm  flexible job shop scheduling problem  nonlinear convergence factor  adaptive weight  variable neighborhood search  elephant herding optimization  EHO  swarm intelligence  individual updating strategy  largescale  benchmark  diversity maintenance  particle swarm optimizer  entropy  large scale optimization  minimum load coloring  memetic algorithm  evolutionary  local search  particle swarm optimization  largescale optimization  adaptive multiswarm  diversity maintenance  deep learning  convolutional neural network  rock types  automatic identification  monarch butterfly optimization  greedy optimization algorithm  global position updating operator  01 knapsack problems
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This book presents an interesting sample of the latest advances in optimization techniques applied to electrical power engineering. It covers a variety of topics from various fields, ranging from classical optimization such as Linear and Nonlinear Programming and Integer and MixedInteger Programming to the most modern methods based on bioinspired metaheuristics. The featured papers invite readers to delve further into emerging optimization techniques and their real application to case studies such as conventional and renewable energy generation, distributed generation, transport and distribution of electrical energy, electrical machines and power electronics, network optimization, intelligent systems, advances in electric mobility, etc.
Cable joint  internal defect  thermal probability density  power system optimization  optimal power flow  developed grew wolf optimizer  energy internet  prosumer  energy management  consensus  demand response  dayahead load forecasting  modular predictor  feature selection  microphasor measurement unit  mutual information theory  stochastic state estimation  twopoint estimation method  JAYA algorithm  multipopulation method (MP)  chaos optimization algorithm (COA)  economic load dispatch problem (ELD)  optimization methods  constrained parameter estimation  extended Kalman filter  power systems  C&I particle swarm optimization  ringdown detection  optimal reactive power dispatch  loss minimization  voltage deviation  hybrid method  tabu search  particle swarm optimization  artificial lighting  simulation  calibration  radiance  GenOpt  street light points  DC optimal power flow  power transfer distribution factors  generalized generation distribution factors  unit commitment  adaptive consensus algorithm  distributed heatelectricity energy management  eight searching subregions  islanded microgrid  dragonfly algorithm  metaheuristic  optimal power flow  particle swarm optimization  CCHP system  energy storage  offdesign performance  dynamic solving framework  battery energy storage system  micro grid  MILP  PCS efficiency  piecewise linear techniques  renewable energy sources  optimal operation  UC  demand bidding  demand response  genetic algorithm  load curtailment  optimization  hybrid renewable energy system  pumpedhydro energy storage  offgrid  optimization  HOMER software  rural electrification  subSaharan Africa  Cameroon  building energy management system  HVAC system  energy storage system  energy flow model  dependability  sustainability  data center  power architectures  optimization  AC/DC hybrid active distribution  hierarchical scheduling  multistakeholders  discrete wind driven optimization  multiobjective optimization  optimal power flow  metaheuristic  wind energy  photovoltaic  smart grid  transformerfault diagnosis  principal component analysis  particle swarm optimization  support vector machine  wind power  integration assessment  interactive load  considerable decomposition  controllable response  SOCP relaxations  optimal power flow  current margins  affine arithmetic  interval variables  optimizingscenarios method  power flow  wind power  active distribution system  virtual power plant  stochastic optimization  decentralized and collaborative optimization  genetic algorithm  multiobjective particle swarm optimization algorithm  artificial bee colony  IEEE Std. 802000  Schwarz’s equation  fuzzy algorithm  radial basis function  neural network  ETAP  distributed generations (DGs)  distribution network reconfiguration  runnerroot algorithm (RRA)  interturn shortedcircuit fault (ISCF)  strong track filter (STF)  linear discriminant analysis (LDA)  switched reluctance machine (SRM)  charging/discharging  electric vehicle  energy management  genetic algorithm  intelligent scatter search  electric vehicles  heterogeneous networks  demand uncertainty  power optimization  Stackelberg game  power system unit commitment  hybrid membrane computing  crossentropy  the genetic algorithm based P system  the biomimetic membrane computing  transient stability  twostage feature selection  particle encoding method  fitness function  power factor compensation  nonsinusoidal circuits  geometric algebra  evolutionary algorithms  electric power contracts  electric energy costs  cost minimization  evolutionary computation  bioinspired algorithms  congestion management  lowvoltage networks  multiobjective particle swarm optimization  affinity propagation clustering  optimal congestion threshold  optimization  magnetic field mitigation  overhead  underground  passive shielding  active shielding  MV/LV substation  n/a
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This book presents an interesting sample of the latest advances in optimization techniques applied to electrical power engineering. It covers a variety of topics from various fields, ranging from classical optimization such as Linear and Nonlinear Programming and Integer and MixedInteger Programming to the most modern methods based on bioinspired metaheuristics. The featured papers invite readers to delve further into emerging optimization techniques and their real application to case studies such as conventional and renewable energy generation, distributed generation, transport and distribution of electrical energy, electrical machines and power electronics, network optimization, intelligent systems, advances in electric mobility, etc.
Cable joint  internal defect  thermal probability density  power system optimization  optimal power flow  developed grew wolf optimizer  energy internet  prosumer  energy management  consensus  demand response  dayahead load forecasting  modular predictor  feature selection  microphasor measurement unit  mutual information theory  stochastic state estimation  twopoint estimation method  JAYA algorithm  multipopulation method (MP)  chaos optimization algorithm (COA)  economic load dispatch problem (ELD)  optimization methods  constrained parameter estimation  extended Kalman filter  power systems  C&I particle swarm optimization  ringdown detection  optimal reactive power dispatch  loss minimization  voltage deviation  hybrid method  tabu search  particle swarm optimization  artificial lighting  simulation  calibration  radiance  GenOpt  street light points  DC optimal power flow  power transfer distribution factors  generalized generation distribution factors  unit commitment  adaptive consensus algorithm  distributed heatelectricity energy management  eight searching subregions  islanded microgrid  dragonfly algorithm  metaheuristic  optimal power flow  particle swarm optimization  CCHP system  energy storage  offdesign performance  dynamic solving framework  battery energy storage system  micro grid  MILP  PCS efficiency  piecewise linear techniques  renewable energy sources  optimal operation  UC  demand bidding  demand response  genetic algorithm  load curtailment  optimization  hybrid renewable energy system  pumpedhydro energy storage  offgrid  optimization  HOMER software  rural electrification  subSaharan Africa  Cameroon  building energy management system  HVAC system  energy storage system  energy flow model  dependability  sustainability  data center  power architectures  optimization  AC/DC hybrid active distribution  hierarchical scheduling  multistakeholders  discrete wind driven optimization  multiobjective optimization  optimal power flow  metaheuristic  wind energy  photovoltaic  smart grid  transformerfault diagnosis  principal component analysis  particle swarm optimization  support vector machine  wind power  integration assessment  interactive load  considerable decomposition  controllable response  SOCP relaxations  optimal power flow  current margins  affine arithmetic  interval variables  optimizingscenarios method  power flow  wind power  active distribution system  virtual power plant  stochastic optimization  decentralized and collaborative optimization  genetic algorithm  multiobjective particle swarm optimization algorithm  artificial bee colony  IEEE Std. 802000  Schwarz’s equation  fuzzy algorithm  radial basis function  neural network  ETAP  distributed generations (DGs)  distribution network reconfiguration  runnerroot algorithm (RRA)  interturn shortedcircuit fault (ISCF)  strong track filter (STF)  linear discriminant analysis (LDA)  switched reluctance machine (SRM)  charging/discharging  electric vehicle  energy management  genetic algorithm  intelligent scatter search  electric vehicles  heterogeneous networks  demand uncertainty  power optimization  Stackelberg game  power system unit commitment  hybrid membrane computing  crossentropy  the genetic algorithm based P system  the biomimetic membrane computing  transient stability  twostage feature selection  particle encoding method  fitness function  power factor compensation  nonsinusoidal circuits  geometric algebra  evolutionary algorithms  electric power contracts  electric energy costs  cost minimization  evolutionary computation  bioinspired algorithms  congestion management  lowvoltage networks  multiobjective particle swarm optimization  affinity propagation clustering  optimal congestion threshold  optimization  magnetic field mitigation  overhead  underground  passive shielding  active shielding  MV/LV substation  n/a
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