Kidney-inspired algorithm for optimization problems

Najmeh Sadat Jaddi, Jafar Alvankarian, Salwani Abdullah

Research output: Contribution to journalArticle

25 Citations (Scopus)

Abstract

In this paper, a population-based algorithm inspired by the kidney process in the human body is proposed. In this algorithm the solutions are filtered in a rate that is calculated based on the mean of objective functions of all solutions in the current population of each iteration. The filtered solutions as the better solutions are moved to filtered blood and the rest are transferred to waste representing the worse solutions. This is a simulation of the glomerular filtration process in the kidney. The waste solutions are reconsidered in the iterations if after applying a defined movement operator they satisfy the filtration rate, otherwise it is expelled from the waste solutions, simulating the reabsorption and excretion functions of the kidney. In addition, a solution assigned as better solution is secreted if it is not better than the worst solutions simulating the secreting process of blood in the kidney. After placement of all the solutions in the population, the best of them is ranked, the waste and filtered blood are merged to become a new population and the filtration rate is updated. Filtration provides the required exploitation while generating a new solution and reabsorption gives the necessary exploration for the algorithm. The algorithm is assessed by applying it on eight well-known benchmark test functions and compares the results with other algorithms in the literature. The performance of the proposed algorithm is better on seven out of eight test functions when it is compared with the most recent researches in literature. The proposed kidney-inspired algorithm is able to find the global optimum with less function evaluations on six out of eight test functions. A statistical analysis further confirms the ability of this algorithm to produce good-quality results.

Original languageEnglish
Pages (from-to)358-369
Number of pages12
JournalCommunications in Nonlinear Science and Numerical Simulation
Volume42
DOIs
Publication statusPublished - 1 Jan 2017

Fingerprint

Kidney
Optimization Problem
Filtration
Test function
Blood
Iteration
Global Optimum
Evaluation Function
Exploitation
Placement
Statistical Analysis
Function evaluation
Objective function
Benchmark
Statistical methods
Necessary
Operator

Keywords

  • Artificial intelligence
  • Kidney-inspired algorithm
  • Meta-heuristics
  • Optimization

ASJC Scopus subject areas

  • Modelling and Simulation
  • Numerical Analysis
  • Applied Mathematics

Cite this

Kidney-inspired algorithm for optimization problems. / Jaddi, Najmeh Sadat; Alvankarian, Jafar; Abdullah, Salwani.

In: Communications in Nonlinear Science and Numerical Simulation, Vol. 42, 01.01.2017, p. 358-369.

Research output: Contribution to journalArticle

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