Search Results - (( sequence optimization search algorithm ) OR ( using application optimization algorithm ))

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  1. 1

    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
    “…In this paper, an approach using Gravitational Search Algorithm (GSA) which is a heuristic optimization algorithm that incorporates the Newton’s law of gravity and the law of motion into analytical studies of systems is proposed to solve the assembly sequence planning problem. …”
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    Conference or Workshop Item
  2. 2

    Product assembly sequence optimization based on genetic algorithm by Yasin, Azman, Puteh, Nurnasran, Daud, Ruslizam, Omar, Mazni, Syed-Abdullah, Sharifah Lailee

    Published 2010
    “…Genetic algorithm (GA) is a search technique used in computing to find approximate solution to optimization and search problem based on the theory of natural selection. …”
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    Article
  3. 3

    A Hybrid Ant-Wolf Algorithm to Optimize Assembly Sequence Planning Problem by M. F. F., Ab Rashid

    Published 2017
    “…Purpose – This paper aims to optimize the assembly sequence planning (ASP) problem using a proposed hybrid algorithm based on Ant Colony Optimization (ACO) and Gray Wolf Optimizer (GWO). …”
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    Article
  4. 4

    A filtering algorithm for efficient retrieving of DNA sequence by Abdul Rahman, Mohd Nordin, Mohd. Saman, Md. Yazid, Ahmad, Aziz, Md. Tap, Abu Osman

    Published 2009
    “…DNA sequence similarity search is an important task in computational biology applications. …”
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    Article
  5. 5

    Multilevel optimization for dense motion estimation by Saaban, Azizan, Kalmoun, El Mostafa, Ibrahim, Haslinda, Ramli, Razamin, Omar, Zurni

    Published 2011
    “…We evaluated the performance of different optimization techniques developed in the context of optical flow computation with different variational models.In particular, based on truncated Newton methods (TN) that have been an effective approach for large-scale unconstrained optimization, we developed the use of efficient multilevel schemes for computing the optical flow.More precisely, we evaluated the performance of a standard unidirectional multilevel algorithm - called multiresolution optimization (MR/Opt), to a bidrectional multilevel algorithm - called full multigrid optimization (FMG/Opt).The FMG/Opt algorithm treats the coarse grid correction as an optimization search direction and eventually scales it using a line search. …”
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    Monograph
  6. 6
  7. 7

    An assembly sequence planning approach with a rule-based multi-state gravitational search algorithm by Ibrahim, I., Ibrahim, Z., Ahmad, Hamzah, Jusof, M.F.M., Yusof, Z.M., Nawawi, S.W., Mubin, M.

    Published 2015
    “…In this paper, an approach based on a new variant of the gravitational search algorithm (GSA) called the rule-based multi-state gravitational search algorithm (RBMSGSA) is used to solve the assembly sequence planning problem. …”
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    Article
  8. 8

    An Assembly Sequence Planning Approach with a Rule-based Multi-state Gravitational Search Algorithm by Ismail, Ibrahim, Zuwairie, Ibrahim, Hamzah, Ahmad, Mohd Falfazli, Mat Jusof, Zulkifli, Md. Yusof, Sophan Wahyudi, Nawawi, Marizan, Mubin

    Published 2015
    “…In this paper, an approach based on a new variant of the gravitational search algorithm (GSA) called the rule-based multi-state gravitational search algorithm (RBMSGSA) is used to solve the assembly sequence planning problem. …”
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    Article
  9. 9

    Sequence t-way test generation using the barnacles mating optimizer algorithm by Kamal Z., Zamli, Kader, Md. Abdul

    Published 2021
    “…More precisely, we focus on the generation of test cases due to the ordering of inputs (or sequence) using the newly developed Barnacles Mating Optimizer (BMO) Algorithm. …”
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    Conference or Workshop Item
  10. 10

    Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence by S. S. S. , Ranjit

    Published 2011
    “…Full search (FS), three step search (TSS), new three step search (NTSS), diamond search (DS) and hexagon based search (HS) are the most well known block-matching algorithm. …”
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    Book Chapter
  11. 11

    Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms by Loo, C.K., Liew, W.S., Seera, M., Lim, Einly

    Published 2015
    “…A genetic algorithm search heuristic was chosen to solve this multi-objective optimization problem. …”
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    Article
  12. 12

    Multi-Objective Discrete Particle Swarm Optimisation Algorithm for Integrated Assembly Sequence Planning and Assembly Line Balancing by M. F. F., Ab Rashid, Hutabarat, Windo, Tiwari, Ashutosh

    Published 2016
    “…In order to optimise an integrated assembly sequence planning and assembly line balancing, this work proposes a multi-objective discrete particle swarm optimisation algorithm that used discrete procedures to update its position and velocity in finding Pareto optimal solution. …”
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    Article
  13. 13

    Automated bilateral negotiation with incomplete information in the e-marketplace. by Jazayeriy, Hamid

    Published 2011
    “…The advantage of the MGT algorithm is that it does not need the exact opponent’s preferences to generate Pareto-optimal offers, instead, it works with a greedy sequence. …”
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    Thesis
  14. 14

    Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line by Noroziroshan, Alireza, Mohd Ariffin, Mohd Khairol Anuar, Ismail, Napsiah

    Published 2010
    “…Then, it started to find the best sequence of jobs for each line based on the generated population by heuristic algorithm. …”
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    Article
  15. 15

    Angle Based Protein Tertiary Structure Prediction Using Bees Optimization Algorithm by Al-Qattan, Zakaria Noor Aldeen Mahmood

    Published 2010
    “…In this project, angles based control with Bees Optimization search algorithm were adopted to search with guidance the protein conformational space in order to find the optimum solution. …”
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    Thesis
  16. 16

    Potential of data minimization techniques approach in improving DNA sequences alignment and comparison / Syed Abdul Mutalib Al Junid … [et al.] by Al Junid, Syed Abdul Mutalib, Haron, Muhammad Adib, Abd Majid, Zulkifli, Othman, Zulkifli

    Published 2012
    “…Specifically, the research objectives are i) to study various DNA sequences alignment algorithms characteristics, architectures and techniques such as scoring functions, optimal alignment and gap; and ii) to investigate the potential of data minimization approach in minimizing the size of data towards discovering the region of similarity in DNA sequences alignment and comparison and iii) to analyze the optimal sequences alignment properties for molecular biology and bioinformatics application. …”
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    Research Reports
  17. 17

    Intergrated multi-objective optimisation of assembly sequence planning and assembly line balancing using particle swarm optimisation by M. F. F., Ab Rashid

    Published 2013
    “…Statistical tests on the algorithms' performance indicates that the proposed MODPSO algorithm presents significant improvement in terms of larger nondominated solution numbers in Pare't o optimal, compared to comparable algorithms including GA based algorithms in both single-model and mixedmodel ASP and ALB problems. …”
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    Thesis
  18. 18

    Particle swarm optimization with partial search to solve traveling salesman problem by Akhand, M.A.H., Akter, Shahina, Rahman, S. Sazzadur, Rahman, M.M. Hafizur

    Published 2012
    “…The objective of the study is to achieve better result introducing using such partial search option for solving TSP. The proposed PSO with Partial Search (PSOPS) algorithm is shown to produce optimal solution within a less number of generation than standard PSO, Genetic Algorithm in solving benchmark TSP.…”
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    Proceeding Paper
  19. 19

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

    Published 2013
    “…Reduction of the search space does not guarantee the optimal solution will be found. …”
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    Thesis
  20. 20

    A genetic algorithm to minimise the maximum lateness on a single machine family scheduling problem by Lee, Lai Soon, Nazif, Habibeh

    Published 2009
    “…The OCGA is compared with other well known local search method namely dynamic length tabu search, randomised steepest descent method, and other variants of genetic algorithms using extensive data sets collected from the literatures. …”
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    Conference or Workshop Item