Search Results - (( loading optimization based algorithm ) OR ( sequence optimisation _ algorithm ))
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A modified artificial bee colony algorithm to optimise integrated assembly sequence planning and assembly line balancing
Published 2019“…Despite many optimisation algorithms that were proposed to optimise this problem, the existing researches on this problem were limited to Evolutionary Algorithm (EA), Ant Colony Optimisation (ACO), and Particle Swarm Optimisation (PSO). …”
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Optimisation of energy efficient Assembly Sequence Planning using Moth-Flame Optimisation alghorithm
Published 2019“…For optimisation purpose, this research proposed a relatively new algorithm called the Moth-Flame Optimisation (MFO). …”
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Multi-Objective Discrete Particle Swarm Optimisation Algorithm for Integrated Assembly Sequence Planning and Assembly Line Balancing
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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Intergrated multi-objective optimisation of assembly sequence planning and assembly line balancing using particle swarm optimisation
Published 2013“…The aim of this research is to establish a methodology and algorithm for integrating ASP and ALB optimisation using Particle Swarm Optimisation. …”
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Development of a Tuneable Test Problem Generator for Assembly Sequence Planning and Assembly Line Balancing
Published 2012“…Numerous research works in assembly sequence planning and assembly line balancing mainly focus on developing algorithms to solve problems and to optimise assembly sequence planning and assembly line balancing. …”
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Multi-objective multi-verse optimiser for integrated two-sided assembly sequence planning and line balancing
Published 2022“…Next, the best MOMVO coefficient was studied, followed by comparing MOMVO performance with well-established multi-objective optimisation algorithms. Finally, a case study problem was presented to demonstrate applicability of the proposed model and algorithm in real-life problem. …”
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An elitist-flower pollination-based strategy for constructing sequence and sequence-less t-way test suite
Published 2018“…If t-way strategies are to be adopted in such a system, there is also a need to support test data generation based on sequence of interactions. In line with such a need, this paper presents a unified strategy based on the new meta-heuristic algorithm, called the elitist flower pollination algorithm (eFPA), for sequence and sequence-less coverage. …”
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Application of the Bees Algorithm to find optimal drill path sequence
Published 2024“…These results show that the Bees Algorithm can be an alternative approach to find the optimal drilling sequence.…”
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Proceeding Paper -
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Optimized PID controller of DC-DC buck converter based on archimedes optimization algorithm
Published 2023“…The algorithm aids in identifying ideal proportional, integral, and derivative gains based on varying load conditions. …”
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One day ahead daily peak hour load forecasting by using invasive weed optimization learning algorithm based Artificial Neural Network
Published 2012“…In this project, an Artificial Neural Network (ANN) trained by the Invasive Weed Optimization (IWO) learning algorithm is proposed for short term load forecasting (STLF) model. …”
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Student Project -
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Performance evaluation and benchmarking of an extended computational model of ant colony system for DNA sequence design
Published 2014“…Ant colony system (ACS) algorithm is one of the biologically inspired algorithms that have been introduced to effectively solve a variety of combinatorial optimisation problems. …”
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Optimisation of multi-stage production-inspection stations using genetic algorithm
Published 2000“…The optimisation tool to be considered is Genetic Algorithm (GA). …”
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An evaluation of network load balancing through Ant Colony Optimization (ACO) based technique / Muhammad Nur Zikri Mohamad Hafizan
Published 2020“…This project works on developing an efficient network load balancing mechanism based on the Ant Colony Optimization (ACO) algorithm. …”
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Student Project -
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Improved bacterial foraging optimization algorithm with machine learning-driven short-term electricity load forecasting: a case study in peninsular Malaysia
Published 2024“…Thus, these parameters of LSSVM need to be chosen appropriately using intelligent optimization algorithms. This study proposes a new hybrid model based on the LSSVM optimized by the improved bacterial foraging optimization algorithm (IBFOA) for forecasting the short-term daily electricity load in Peninsular Malaysia. …”
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Improved bacterial foraging optimization algorithm with machine learning driven short term electricity load forecasting: A case study in Peninsular Malaysia
Published 2024“…Thus, these parameters of LSSVM need to be chosen appropriately using intelligent optimization algorithms. This study proposes a new hybrid model based on the LSSVM optimized by the improved bacterial foraging optimization algorithm (IBFOA) for forecasting the short‑term daily electricity load in Peninsular Malaysia. …”
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Optimized Load Balancing based Task Scheduling in Cloud Environment
Published 2014“…In this paper, task scheduling strategy based on load balancing Quantum Particles Swarm algorithm (BLQPSO) was proposed. …”
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Power system network splitting and load frequency control optimization using ABC based algorithms / Kanendra Naidu a/l Vijyakumar
Published 2015“…This research presents a modified optimization program for the system splitting problem in large scale power system based on Artificial Bee Colony algorithm and graph theory. …”
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Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…This research proposes an enhancement of the ant colony optimization algorithm that caters for dynamic scheduling and load balancing in the grid computing system. …”
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Monograph -
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Improved Bat Algorithm for faster convergence in solving optimisation problem
Published 2021“…Therefore, this confirms the validity of the IBA as an alternative algorithm for solving optimisation problems.…”
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