Search Results - (( sequence optimization strategy algorithm ) OR ( sequence optimization modified algorithm ))

BASE: a bacteria foraging algorithm for cell formation with sequence data by Nouri, Hossein, Tang, Sai Hong, Baharudin, B. T. Hang Tuah, Mohd Ariffin, Mohd Khairol Anuar

“…In addition, a newly developed BFA-based optimization algorithm for CF based on operation sequences is discussed. …”
Get full text
Get full text
Get full text

A hybrid of differential search algorithm and flux balance analysis to: Identify knockout strategies for in silico optimization of metabolites production by Daud K.M., Zalmiyah Zakaria, Zuraini Ali Shah, Mohd Saberi Mohamad, Safaai Deris, Omatu S., Juan Manuel Corchado Rodríguez

Get full text
Get full text

The development of integrated planning and scheduling framework for dynamic and reactive environment of complex manufacturing problem by Zakaria, Zalmiyah, Deris, Safaai, Mat Yatim, Safie, Othman, Muhamad Razib

“…Next, multi-population directed genetic algorithms (MDGA) have been used to generate a number of optimal operation sequences for a real world manufacturing problem which is elaborated in Chapter 3. …”
Get full text
Get full text
Get full text

Simulated Kalman Filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem by Suhazri Amrin, Rahmad, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

“…Researchers have worked on ideas to improve exploration capability to prevent premature convergence by trying prediction operators, opposition-based learning, and different iteration strategies. There were also attempts to hybridize SKF with other famous algorithms such as Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), and Sine Cosine Algorithm (SCA) to improve its performance. …”
Get full text
Get full text
Get full text
Get full text

Hybrid dynamic scheduling model for flexible manufacturing system with machine availability and new job arrivals by Paslar, Shahla

“…The hybrid rescheduling strategy takes into account the affected operation rescheduling (AOR) strategy and BBO-VNS match-up approaches to handle machine breakdown and accommodates new arrived order without changing the sequence of operations on machines. …”
Get full text
Get full text

Modified Harris Hawks Optimization Algorithm For Protein Multiple Sequence Alignment by Ibrahim, Al-Zaidi Mohammed Khaleel

Get full text
Get full text

Sequence and sequence-less t-way test suite generation strategy based on the elitist flower pollination algorithm by Mohammed Abdullah, Abdullah Nasser

“…Addressing these aforementioned issues and complementing the existing sequence based strategies such as t-SEQ, Sequence Covering Array Generator and Bee Algorithm, this thesis presents a unified strategy based on the new meta-heuristic algorithm, called the Elitist Flower Pollination Algorithm (eFPA). …”
Get full text
Get full text

Development of Genetic Algorithm Procedure for Sequencing Problem in Mixed-Model Assembly Lines by Noroziroshan, Alireza

“…It confirms that the proposed genetic algorithm procedure is able to tackle the problem complexity and reach to optimal solutions in different production strategies. …”
Get full text
Get full text

Operation sequencing using modified particle swarm optimization by Zakaria, Zalmiyah, Deris, Safaai

“…In this paper, modified particle swarm optimization (MPSO) has been used to generate a feasible operation sequence for a real world manufacturing problem. …”
Get full text
Get full text
Get full text

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

“…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. …”
Get full text
Get full text
Get full text
Get full text

Simulated kalman filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem by Suhazri Amrin, Rahmad, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

Get full text
Get full text
Get full text
Get full text

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

“…To improve the performance of the swap sequence based PSO, this paper introduces an Enhanced Swap Sequence based PSO (Enhanced SSPSO) algorithm by integrating the strategies of the Expanded PSO (XPSO) in the swap sequence based PSO. …”
Get full text
Get full text
Get full text
Get full text
Get full text

Evaluating Bees Algorithm for Sequence-based T-way Testing Test Data Generation by M. H., Mohamed Zabil, Kamal Z., Zamli, K. C., Lim

“…This paper presents statistical analysis on the performance of Bees Algorithm against the other sequence t-way strategies, in order to generate test cases.…”
Get full text
Get full text
Get full text

T-way strategy for sequence input interactions test case generation adopting fish swarm algorithm by Rahman, Mostafijur, Sultana, Dalia, Sabira, Khatun, M. F. M., Jusof, Syamimi Mardiah, Shaharum, Nurhafizah, Abu Talip Yusof, Qaiduzzaman, Khandker M., Hasan, Md. Hasibul, Rahman, Md. Mushfiqur, Hossen, Md. Anwar, Begum, Afsana

“…The reason is that the T-way sequence input interaction is NP-Hard problem. In this research, Fish Swarm algorithm is proposed to adapt with T-way sequence input interaction test strategy. …”
Get full text
Get full text
Get full text

Modified firefly algorithm for directional overcurrent relay coordination in power system protection / Muhamad Hatta Hussain by Hussain, Muhamad Hatta

“…The objectives of the studies are to develop a new optimization technique termed as Modified Firefly Algorithm (MFA) for minimizing the relay operating time, to develop a Multi-Objective Modified Firefly Algorithm (MOMFA) for minimizing both the total relay operating time and relay coordination time and to develop an integrated optimal predictor termed as Modified Firefly Algorithm-Artificial Neural Network (MFA-ANN) for accurate prediction of relay operating time. …”
Get full text
Get full text

Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach by Wan Solehah, Wan Ahmad

“…Hence, this research’s objective aimed to propose an optimization strategy based on Structural Modification and Optimizing Training Network for improving the lacking of accuracy of response in the chatbot application, to propose the algorithm enhancement to improve the current attention mechanism in the Attentive Sequence-to-Sequence model and the network’s training optimization of its inability to memorize the dialogue history, and lastly, to evaluate the accuracy of response of the proposed solution through data training on loss function and real data testing. …”
Get full text
Get full text
Get full text
Get full text

Studying the Impact of Initialization for Population-Based Algorithms with Low-Discrepancy Sequences by Adnan Ashraf, Sobia Pervaiz, Waqas Haider Bangyal, Kashif Nisar, Ag. Asri Ag. Ibrahim, Joel J. P. C. Rodrigues, Danda B. Rawat

“…To solve different kinds of optimization challenges, meta-heuristic algorithms have been extensively used. …”
Get full text
Get full text
Get full text
Get full text
Get full text

Optimization of job scheduling in a machine shop using genetic algorithm by Adhikari, A., Biswas, C.K., Adhikari, N.

“…A modified version of GA known as string GA has been used to get the near optimal cycle time for permutation analysis. …”
Get full text
Get full text

Optimization of job scheduling in a machine shop using genetic algorithm by Adhikari, A., Biswas, C.K., Adhikari, N.

“…A modified version of GA known as string GA has been used to get the near optimal cycle time for permutation analysis. …”
Get full text
Get full text

Process Sequencing Modeled as TSP with Precedence Constraints - A Genetic Algorithm Approach by N. M., Razali

“…The developed GA procedure improved the performance of the algorithm with less number of generations and less convergence time in achieving optimal solutions. …”
Get full text
Get full text
Get full text