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bee_dynamics.jl
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bee_dynamics.jl
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mutable struct Bee{T}
sol::T
fit::Float64
t::Int
end
Bees = Array{Bee, 1}
Bee(solution) = Bee(solution, fit(solution.f), 0)
"""
get_position(bee)
Get the position vector of a bee when optimize using ABC algorithm.
"""
get_position(bee::Bee) = bee.sol.x
"""
fval(solution)
Get the fitness of a bee when optimize using ABC algorithm.
"""
fval(bee::Bee) = bee.sol.f
Base.show(io::IO, ::MIME"text/html", pop::Vector{Bee{xf_indiv}}) = show(io, "text/html", [p.sol for p in pop])
minimum(st::State{Bee{xf_indiv}}) = st.best_sol.sol.f
minimum(st::State{Bee{xfgh_indiv}}) = st.best_sol.sol.f
minimizer(st::State{Bee{xf_indiv}}) = st.best_sol.sol.x
minimizer(st::State{Bee{xfgh_indiv}}) = st.best_sol.sol.x
@inline function updateFit!(bee::Bee)
bee.fit = fit(bee.sol.f)
end
@inline function updateFit!(bees::Bees)
for bee in bees
updateFit!(bee)
end
end
function fit(fx)
if fx >= 0.0
return 1.0/(1.0+fx)
end
1.0 + abs(fx)
end
function updateBee!(bee, bee2, problem)
D = length(bee.sol.x)
ϕ = -1.0 + 2.0rand()
v = ϕ*(bee.sol.x - bee2.sol.x)
x_new = bee.sol.x + v
replace_with_random_in_bounds!(x_new, problem.bounds)
new_sol = create_solution(x_new, problem)
if is_better(new_sol, bee.sol) #fx < bee.sol.f
bee.sol = new_sol
bee.fit = fit(new_sol.f)
bee.t = 0
else
bee.t += 1
end
end
function getK(i, N)
j = rand(1:N)
while j == i
j = rand(1:N)
end
j
end
function employedPhase!(bees, problem, Ne)
N = length(bees)
for i in randperm(N)[1:Ne]
updateBee!(bees[i], bees[getK(i, N)], problem)
end
end
function roulettSelect(bees, sum_f)
r = rand()
rs = 0.0
for i in 1:length(bees)
rs += bees[i].fit / sum_f
if r <= rs
return i
end
end
return length(bees)
end
function outlookerPhase!(bees, problem, No::Int)
N = length(bees)
sum_f = sum(map(x->x.fit, bees))
for i=1:No
j = roulettSelect(bees, sum_f)
updateBee!(bees[j], bees[getK(j, N)], problem)
end
end
function scoutPhase!(bees, problem, genPos::Function, limit::Int)
bees_scout = filter(x->x.t >= limit, bees)
for i in 1:length(bees_scout)
bees_scout[i].sol = create_solution(genPos(), problem)
bees_scout[i].t = 0
end
return length(bees_scout)
end
function getBestBee(bees)
best = bees[1]
for bee in bees
if bee.sol.f < best.sol.f
best = bee
end
end
return best
end
function chooseBest(bees, best)
bee_cand = getBestBee(bees)
if bee_cand.sol.f < best.sol.f
return deepcopy(bee_cand)
end
return best
end
function initialbees(N, problem)
P = generate_population(N, problem)
return [ Bee(sol) for sol in P ]
end