Search Results - (( sequence optimization _ algorithm ) OR ( evolution optimization modified algorithm ))

Search alternatives:

Refine Results
  1. 1
    Hybrid genetic algorithm with multi-parents recombination for job shop scheduling problems / Ong Chung Sin

    Hybrid genetic algorithm with multi-parents recombination for job shop scheduling problems / Ong Chung Sin by Ong, Chung Sin

    Published 2013
    “…Metaheuristic is one of the “approximation methods” that is able to find practically acceptable solutions especially for large-scale problems within a limited amount of time. Genetic Algorithms (GA) which is based on biological evolution is one of the metaheuristics that has been successfully applied to JSSP. …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  2. 2
    A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising

    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
    “…A modified crossover scheme called rand-length crossover was designed to fit the proposed variable-length DE, and the new DE algorithm is referred to as the random variable-length crossover differential evolution (rvlx-DE) algorithm. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  3. 3
    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain

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

    Published 2018
    “…This modified algorithm called Modified Multi-Objective Particle Swarm Optimization (M-MOPSO) employs a fixed-sized external archive along with a dynamic boundary-based search mechanism to evolve the population. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  4. 4
    A refined differential evolution algorithm for improving the performance of optimization process

    A refined differential evolution algorithm for improving the performance of optimization process by A. R., Yusoff, Nafrizuan, Mat Yahya

    Published 2011
    “…Various Artificial Intelligent (AI) algorithms can be applied in solving optimization problems. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  5. 5
    Improved chemotaxis differential evolution optimization algorithm

    Improved chemotaxis differential evolution optimization algorithm by Yıldız, Y. Emre, Altun, Oğuz, Topal, A. Osman

    Published 2015
    “…The social foraging behavior of Escherichia coli has recently received great attention and it has been employed to solve complex search optimization problems.This paper presents a modified bacterial foraging optimization BFO algorithm, ICDEOA (Improved Chemotaxis Differential Evolution Optimization Algorithm), to cope with premature convergence of reproduction operator.In ICDEOA, reproduction operator of BFOA is replaced with probabilistic reposition operator to enhance the intensification and the diversification of the search space.ICDEOA was compared with state-of-the-art DE and non-DE variants on 7 numerical functions of the 2014 Congress on Evolutionary Computation (CEC 2014). …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  6. 6
    Broadening selection competitive constraint handling algorithm for faster convergence

    Broadening selection competitive constraint handling algorithm for faster convergence by Shaikh, T.A., Hussain, S.S., Tanweer, M.R., Hashmani, M.A.

    Published 2020
    “…In this study, the BSCCH algorithm has been coupled with Differential Evolution algorithm as a proof of concept because it is found to be an efficient algorithm in the literature for constrained optimization problems. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  7. 7
    Application of genetic algorithm methods to optimize flowshop sequencing problem

    Application of genetic algorithm methods to optimize flowshop sequencing problem by Mohd Fadil, Md Sairi

    Published 2008
    “…Application of genetic algorithm method to optimize flow shop sequencing problem as the title of this project is the study about the method used in order to optimize flow shop sequencing problem. …”
    Get full text
    Get full text
    Undergraduates Project Papers
    Save to List
    Saved in:
  8. 8
    Assembly sequence optimization using the bees algorithm

    Assembly sequence optimization using the bees algorithm by Kamaruddin, Shafie, Azmi, Nabilah, Sukindar, Nor Aiman

    Published 2022
    “…As a result, the Bees Algorithm outperforms other algorithms in dealing with the multi-modal optimization problem of assembly sequence optimization.…”
    Get full text
    Get full text
    Get full text
    Get full text
    Book Chapter
    Save to List
    Saved in:
  9. 9
    Multiple Objective Optimization of Green Logistics Using Cuckoo Searching Algorithm

    Multiple Objective Optimization of Green Logistics Using Cuckoo Searching Algorithm by Wang, Wei, Liu, Yao

    Published 2016
    “…In this paper, a modified Cuckoo searching algorithm is proposed to solve the multiple objective Green Logistics optimization problem. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  10. 10
    An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP

    An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP by Bibi Aamirah Shafaa Emambocus, Muhammed Basheer Jasser, Muzaffar Hamzah, Aida Mustapha, Angela Amphawan

    Published 2021
    “…To evaluate the proposed algorithm, the solutions to the TSP problem obtained from the proposed algorithm and swap sequence based PSO are compared in terms of the best solution, mean solution, and time taken to converge to the optimal solution. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  11. 11
    Self-configured link adaptation using channel quality indicator-modulation and coding scheme mapping with partial feedback for green long-term evolution cellular systems

    Self-configured link adaptation using channel quality indicator-modulation and coding scheme mapping with partial feedback for green long-term evolution cellular systems by Salman, Mustafa Ismael

    Published 2015
    “…To achieve this objective, an iterative approach based on swarm intelligence is used to find the optimal CQI threshold at which the competing criteria are optimized. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  12. 12
    A centralized localization algorithm for prolonging the lifetime of wireless sensor networks using particle swarm optimization in the existence of obstacles

    A centralized localization algorithm for prolonging the lifetime of wireless sensor networks using particle swarm optimization in the existence of obstacles by Abdulhasan Al-Jarah, Ali Husam

    Published 2017
    “…So, the travelling distance, power consumption and lifetime of the network will be calculated in both cases for original algorithm and modified algorithm, which is a modified deployment algorithm, and compared between them. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  13. 13
    A multi-objective particle swarm optimization algorithm based on dynamic boundary search for constrained optimization

    A multi-objective particle swarm optimization algorithm based on dynamic boundary search for constrained optimization by Mohd Zain, Mohamad Zihin, Kanesan, Jeevan, Chuah, Joon Huang, Dhanapal, Saroja, Kendall, Graham

    Published 2018
    “…M-MOPSO is compared with four other algorithms namely, MOPSO, Multi-Objective Grey Wolf Optimizer (MOGWO), Multi-Objective Evolutionary Algorithm based on Decompositions (MOEA/D) and Multi-Objective Differential Evolution (MODE). …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  14. 14
    OPTIMIZATION OF HYBRID-FUZZY CONTROLLER FOR SERVOMOTOR CONTROL USING A MODIFIED GENETIC ALGORITHM

    OPTIMIZATION OF HYBRID-FUZZY CONTROLLER FOR SERVOMOTOR CONTROL USING A MODIFIED GENETIC ALGORITHM by WAHYUNGGORO, OYAS WAHYUNGGORO

    Published 2011
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  15. 15
    Autotuning PID Controllers for Quadplane Hybrid UAV using Differential Evolution Algorithm

    Autotuning PID Controllers for Quadplane Hybrid UAV using Differential Evolution Algorithm by Pairan, Mohammad Fahmi, Shamsudin, Syariful Syafiq

    Published 2024
    “…By iteratively modifying the control settings to achieve optimal performance, the DE algorithm replaces the requirement for manual PID tuning, which can be time-consuming and suboptimal. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  16. 16
    Autotuning PID Controllers for Quadplane Hybrid UAV using Differential Evolution Algorithm

    Autotuning PID Controllers for Quadplane Hybrid UAV using Differential Evolution Algorithm by Pairan, Mohammad Fahmi, Shamsudin, Syariful Syafiq, Yaakub, Mohd Fauzi

    Published 2024
    “…By iteratively modifying the control settings to achieve optimal performance, the DE algorithm replaces the requirement for manual PID tuning, which can be time-consuming and suboptimal. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  17. 17
    Comparative Analysis of Low Discrepancy Sequence-Based Initialization Approaches Using Population-Based Algorithms for Solving the Global Optimization Problems

    Comparative Analysis of Low Discrepancy Sequence-Based Initialization Approaches Using Population-Based Algorithms for Solving the Global Optimization Problems by Waqas Haider Bangyal, Kashif Nisar, Ag. Asri Bin Ag. Ibrahim, Muhammad Reazul Haque, Joel J. P. C. Rodrigues, Danda B. Rawat

    Published 2021
    “…These algorithms can influence the convergence to find an efficient optimal solution. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  18. 18
    Assessment of integrated assembly sequence planning and line balancing optimization using metaheuristic algorithms

    Assessment of integrated assembly sequence planning and line balancing optimization using metaheuristic algorithms by Mohd Fadzil Faisae, Ab Rashid, Ullah, Wasif, Muhammad Ammar, Nik Mu’tasim

    Published 2024
    “…These algorithms include Genetic Algorithm (GA), Ant Colony Optimization (ACO), and Particle Swarm Optimization (PSO). …”
    Get full text
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  19. 19
    Gravitational Search Algorithm for Assembly Sequence Planning

    Gravitational Search Algorithm for Assembly Sequence Planning by Ismail, Ibrahim, Zuwairie, Ibrahim, Hamzah, Ahmad, Mohd Falfazli, Mat Jusof, Zulkifli, Md. Yusof, Sophan Wahyudi, Nawawi, Marizan, Mubin

    Published 2014
    “…Thus, it is needed to find the optimal sequence from the feasible assembly sequences. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  20. 20
    Application of the Bees Algorithm to find optimal drill path sequence

    Application of the Bees Algorithm to find optimal drill path sequence by Zainal Abidin, Muhammad Harith, Kamaruddin, Shafie, Adam Malek, Afiqah, Sukindar, Nor Aiman

    Published 2024
    “…These results show that the Bees Algorithm can be an alternative approach to find the optimal drilling sequence.…”
    Get full text
    Get full text
    Get full text
    Get full text
    Proceeding Paper
    Save to List
    Saved in:

Search Tools: