Cost and fuel-optimal selection of HEV topologies using Particle Swarm Optimization and Dynamic Programming

2012 ◽  
Author(s):  
T. Nuesch ◽  
T. Ott ◽  
S. Ebbesen ◽  
L. Guzzella
Keyword(s):  
Dynamic Programming ◽  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Optimal Selection ◽  
Swarm Optimization ◽  
Selection Of

scholarly journals Resolving the optimal selection of a natural reserve using the particle swarm optimisation by applying transfer functions

2018 ◽  
Author(s):  
Boris Almonacid
Keyword(s):  
Particle Swarm Optimization ◽  
Transfer Functions ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Optimal Selection ◽  
Metaheuristic Algorithm ◽  
Swarm Optimization ◽  
Natural Reserve ◽  
Transfer Method ◽  
Selection Of

The optimal selection of a natural reserve (OSRN) is an optimisation problem with a binary domain. To solve this problem the metaheuristic algorithm Particle Swarm Optimization (PSO) has been chosen. The PSO algorithm has been designed to solve problems in real domains. Therefore, a transfer method has been applied that converts the equations with real domains of the PSO algorithm into binary results that are compatible with the OSRN problem. Four transfer functions have been tested in four case studies to solve the OSRN problem. According to the tests carried out, it is concluded that two of the four transfer functions are apt to solve the problem of optimal selection of a natural reserve.

scholarly journals Resolving the optimal selection of a natural reserve using the particle swarm optimisation by applying transfer functions

2018 ◽  
Author(s):  
Boris L Almonacid
Keyword(s):  
Particle Swarm Optimization ◽  
Transfer Functions ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Optimal Selection ◽  
Metaheuristic Algorithm ◽  
Swarm Optimization ◽  
Natural Reserve ◽  
Transfer Method ◽  
Selection Of

The optimal selection of a natural reserve (OSRN) is an optimisation problem with a binary domain. To solve this problem the metaheuristic algorithm Particle Swarm Optimization (PSO) has been chosen. The PSO algorithm has been designed to solve problems in real domains. Therefore, a transfer method has been applied that converts the equations with real domains of the PSO algorithm into binary results that are compatible with the OSRN problem. Four transfer functions have been tested in four case studies to solve the OSRN problem. According to the tests carried out, it is concluded that two of the four transfer functions are apt to solve the problem of optimal selection of a natural reserve.

scholarly journals Resolving the optimal selection of a natural reserve using the particle swarm optimisation by applying transfer functions

2018 ◽  
Author(s):  
Boris Almonacid
Keyword(s):  
Particle Swarm Optimization ◽  
Transfer Functions ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Optimal Selection ◽  
Metaheuristic Algorithm ◽  
Swarm Optimization ◽  
Natural Reserve ◽  
Transfer Method ◽  
Selection Of

The optimal selection of a natural reserve (OSRN) is an optimisation problem with a binary domain. To solve this problem the metaheuristic algorithm Particle Swarm Optimization (PSO) has been chosen. The PSO algorithm has been designed to solve problems in real domains. Therefore, a transfer method has been applied that converts the equations with real domains of the PSO algorithm into binary results that are compatible with the OSRN problem. Four transfer functions have been tested in four case studies to solve the OSRN problem. According to the tests carried out, it is concluded that two of the four transfer functions are apt to solve the problem of optimal selection of a natural reserve.

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