Search Results - (( _ optimization (problems OR problem) algorithm ) OR ( evolution optimization method algorithm ))

Refine Results
  1. 1

    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain by Mohamad Zihin , Mohd Zain

    Published 2018
    “…The proposed method is tested on 10 multi-objective benchmark problems of CEC 2009 and compared with four metaheuristics: Multi-Objective Grey Wolf Optimizer (MOGWO), Multi-Objective Evolutionary Algorithm Based on Decomposition (MOEA/D), Multi-Objective Differential Evolution (MODE) and MOPSO. …”
    Get full text
    Get full text
    Thesis
  2. 2

    Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem by Anniza, Hamdan, San Nah, Sze, Say Leng, Goh, Kang Leng, Chiew, Wei King, Tiong

    Published 2023
    “…Other metaheuristic approaches such as genetic algorithm, differential evolution algorithm, particle swarm optimization, and ant colony optimization are still preferable to address combinatorial optimization problems. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  3. 3

    A holistic review on artificial intelligence techniques for well placement optimization problem by Islam, J., Vasant, P.M., Negash, B.M., Laruccia, M.B., Myint, M., Watada, J.

    Published 2020
    “…Nature-inspired gradient-free optimization algorithms like particle swarm optimization, genetic algorithm, covariance matrix adaptation evolution strategy and differential evolution have been utilized in this area. …”
    Get full text
    Get full text
    Article
  4. 4

    A hybrid SP-QPSO algorithm with parameter free adaptive penalty method for constrained global optimization problems by Fatemeh, D. B., Loo, C. K., Kanagaraj, G., Ponnambalam, S. G.

    Published 2018
    “…This paper attempts the suitability of newly developed hybrid algorithm, Shuffled Complex Evolution with Quantum Particle Swarm Optimization abbreviated as SP-QPSO, extended specifically designed for solving constrained optimization problems. …”
    Get full text
    Get full text
    Get full text
    Article
  5. 5

    An algorithmic framework for multiobjective optimization by Ganesan, T., Elamvazuthi, I., Shaari, K.Z.K., Vasant, P.

    Published 2013
    “…Various metaheuristic techniques such as differential evolution (DE), genetic algorithm (GA), gravitational search algorithm (GSA), and particle swarm optimization (PSO) have been used in conjunction with scalarization techniques such as weighted sum approach and the normal-boundary intersection (NBI) method to solve MO problems. …”
    Get full text
    Get full text
    Article
  6. 6

    A New Hybrid Approach Based On Discrete Differential Evolution Algorithm To Enhancement Solutions Of Quadratic Assignment Problem by Asaad Shakir, Hameed, Mohd Aboobaider, Burhanuddin, Mutar, Modhi Lafta, Ngo, Hea Choon

    Published 2020
    “…The Combinatorial Optimization Problem (COPs) is one of the branches of applied mathematics and computer sciences, which is accompanied by many problems such as Facility Layout Problem (FLP), Vehicle Routing Problem (VRP), etc. …”
    Get full text
    Get full text
    Get full text
    Article
  7. 7

    Multiobjective optimization of bioethanol production via hydrolysis using hopfield- enhanced differential evolution by Ganesan, T., Elamvazuthi, I., Shaari, K.Z.K., Vasant, P.

    Published 2014
    “…In this chapter, the weighted sum scalarization approach is used in conjunction with three meta-heuristic algorithms: Differential Evolution (DE), Hopfield-Enhanced Differential Evolution (HEDE), and Gravitational Search Algorithm (GSA). …”
    Get full text
    Get full text
    Book
  8. 8
  9. 9

    An improved method using fuzzy system based on hybrid boahs for phishing attack detection by Noor Syahirah, Nordin

    Published 2022
    “…Moreover, Butterfly Optimization Algorithm and Harmony Search Algorithm were combined as optimization method led to a new method named BOAHS. …”
    Get full text
    Get full text
    Thesis
  10. 10

    Sub-route reversal repair mechanism and differential evolution for urban transit network design problem by Tarajo, Buba Ahmed

    Published 2017
    “…This thesis considers the urban transit network design problem (UTNDP) focusing on the implementation of population-based metaheuristic approaches, specifically on differential evolution (DE) and particle swarm optimization (PSO). …”
    Get full text
    Get full text
    Thesis
  11. 11

    Performances Of Metaheuristic Algorithms In Optimizing Tool Capacity Allocations by Goheannee

    Published 2014
    “…In this research, the algorithms studied includes Genetic Algorithm, Particle Swarm Optimization Algorithm, Differential Evolution Algorithm, Harmony Search Algorithm, Teaching-LearningBased Optimization Algorithm and Black Hole Algorithm. …”
    Get full text
    Get full text
    Thesis
  12. 12
  13. 13

    Representation Of Rational Bézier Quadratics Using Genetic Algorithm, Differential Evolution And Particle Swarm Optimization by Yahya, Zainor Ridzuan

    Published 2013
    “…Three soft computing techniques namely Genetic Algorithm (GA), Differential Evolution (DE) and Particle Swarm Optimization (PSO) are utilized for the desired manipulation of curves and surfaces. …”
    Get full text
    Get full text
    Thesis
  14. 14

    A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising by Al-Dabbagh, Mohanad Dawood, Al-Dabbagh, Rawaa Dawoud, Raja Abdullah, Raja Syamsul Azmir, Hashim, Fazirulhisyam

    Published 2015
    “…As the standard DE algorithm is a fixed length optimizer, it is not suitable for solving signal de-noising problems that call for variability. …”
    Get full text
    Get full text
    Article
  15. 15

    Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

    Published 2008
    “…Three programs have developed; Differential Evolution Neural Network (DENN), Genetic Algorithm Neural Network (GANN) and Particle Swarm Optimization with Neural Network (PSONN) to probe the impact of these methods on ANN learning using various datasets. …”
    Get full text
    Get full text
    Get full text
    Thesis
  16. 16
  17. 17

    Development of heuristic methods based on genetic algorithm (GA) for solving vehicle routing problem by Ismail, Zuhaimy, Nurhadi, Irhamah, Zainuddin, Zaitul Marlizawati

    Published 2008
    “…The Vehicle Routing Problem (VRP) is an important area and has been studied as combinatorial optimization problems. …”
    Get full text
    Get full text
    Monograph
  18. 18

    Optimized differential evolution algorithm for linear frequency modulation radar signal denoising by Al-Dabbagh, Mohanad Dawood Hasan

    Published 2013
    “…The standard DE algorithm is known as a fixed length optimizer, while our problem demands the need for methods that aren’t tolerated to a fixed individual size, and that was made by altering the mutation and crossover strategies as well as the selection operation. …”
    Get full text
    Get full text
    Thesis
  19. 19

    Economic power dispatch solutions incorporating stochastic wind power generators by moth flow optimizer by Alam, Mohammad Khurshed, Mohd Herwan, Sulaiman, Sayem, Md. Shaoran, Khan, Rahat

    Published 2023
    “…This study's primary purpose is to apply state-of-the-art variations of the differential evolution (DE) algorithm for single-objective optimization and selected evolutionary algorithms for multi-objective optimization issues in power systems. …”
    Get full text
    Get full text
    Get full text
    Article
  20. 20

    Multiobjective design optimization of a nano-CMOS voltage-controlled oscillator using game theoretic-differential evolution by Ganesan, T., Elamvazuthi, I., Vasant, P.

    Published 2015
    “…The weighted sum scalarization approach was employed in this work in conjunction with three metaheuristic algorithms: particle swarm optimization (PSO), differential evolution (DE) and the improved DE algorithm (GTDE) (which was enhanced using ideas from evolutionary game theory). …”
    Get full text
    Get full text
    Article