A Clojure library designed to optimize function by SHADE(Success-History Based Parameter Adaptation for Differential Evolution). This library's SHADE targets to minimize objective function which takes vector of continuous value then returns number.
SHADE was proposed below a paper.
Ryoji Tanabe and Alex Fukunaga. "Success-history based parameter adaptation for differential evolution." In 2013 IEEE congress on evolutionary computation, pp. 71-78. IEEE, 2013.
As far as I know, SHADE is one of the best optimization algorithm for function optimization which means single objective and continuous problems.
(ns your-ns.core
(:require [shade.core :as shade]))
(defn rastrigin-function
[A theta x]
(let [n (count x)]
(+ (* A n)
(->> x
(map #(- (* %1 %1) (* A (Math/cos (* theta Math/PI %1)))))
(apply +)))))
(def evaluate-function (partial rastrigin-function 10.0 2.0))
(def population-size 50)
(def max-generation 1000)
;; A dimension of the solution.
(def dimension-of-problem 2)
;; A domain of the evaluate(objective) function.
(def min-search-range -5)
(def max-search-range 5)
(def last-generation-population
(shade/run population-size dimension-of-problem min-search-range max-search-range evaluate-function max-generation))
(def best-solution (first (sort-by :shade.core/fitness last-generation-population)))
(println best-solution)
;; #:shade.core{:scaling-factor 0.9085399934900505, :improved-fitness 7.105427357601002E-15, :crossover-rate 0.7407592708749081, :fitness 0.0, :data (-5.490531981246176E-10 -6.889619712813397E-10)}
(def best-solution-fitness (:shade.core/fitness best-solution))
(println best-solution-fitness)
;; 0.0
(def best-solution-data (:shade.core/data best-solution))
(println best-solution-data)
;; (-5.490531981246176E-10 -6.889619712813397E-10)MIT License
Copyright 2020 Ryota Miyoshi
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