Search Results - (( using optimisation search algorithm ) OR ( using optimization problems algorithm ))
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Symbiotic organisms search optimization algorithm in cloud computing: a nature-inspired meta-heuristic
Published 2022“…In the past few years nature-inspired algorithms are experiencing rapid growth where most optimisation problems in different domains are addressed using it. …”
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Optimised Crossover Genetic Algorithms for Combinatorial Optimisation Problems
Published 2010“…This thesis focuses on the development of a new stream of crossover within genetic algorithms, called Optimised Crossover Genetic Algorithm (OCGA) for solving combinatorial optimisation problems, which takes into account the objective function in finding the best ofspring solution among an exponentially large number of potential ofspring. …”
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A modified flower pollination algorithm and carnivorous plant algorithm for solving engineering optimization problem
Published 2021“…Hence, using an effective optimiser to solve these problems with high complexity is important. …”
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Optimization Of Pid Controller Using Grey Wolf Optimzer And Dragonfly Algorithm
Published 2018“…In this research, swarming intelligence is used to solve optimisation problem. Grey Wolf Optimizer and Dragonfly Algorithm were chosen. …”
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Monograph -
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Design Of Perturbative Hyper-Heuristics For Combinatorial Optimisation
Published 2019“…Approaches for solving combinatorial optimisation problems can be separated into two main sub-classes, i.e. exact and approximation algorithms. …”
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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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Application of a primal-dual interior point algorithm using exact second order information with a novel non-monotone line search method to generally constrained minimax optimization problems
Published 2008“…This work presents the application of a primal-dual interior point method to minimax optimisation problems. The algorithm differs significantly from previous approaches as it involves a novel non-monotone line search procedure, which is based on the use of standard penalty methods as the merit function used for line search. …”
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Development of multi-objective Chaotic Immune Symbiotic Organisms Search (CISOS) algorithm for facts device installation in voltage security control / Mohamad Khairuzzaman Mohamad...
Published 2019“…It is proposed that CISOS technique is used to solve other optimisation problems for future research.…”
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Synthesis of transistor-chaining algorithm for CMOS cell layout using bipartite graph / Azizi Misnan
Published 1997“…A depth - first search algorithm is used to search for optimal chaining. …”
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An improved leader particle swarm optimisation algorithm for solving flexible ac transmission systems optimisation problem in power system
Published 2014“…The results of applying improved leader PSO to IEEE 14 bus power system shows its significant outperformance over six other optimisation algorithms including conventional PSO, mutated PSO, enhanced PSO, harmony search,genetic algorithm and gravitational search algorithm. …”
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An enhanced discrete symbiotic organism search algorithm for optimal task scheduling in the cloud
Published 2021“…Our proposed algorithm is an extension of the standard symbiotic organism search (SOS), a nature-inspired algorithm that has been implemented to solve various numerical optimisation problems. …”
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Multi-objective optimisation of assembly line balancing type-e problem with resource constraints
Published 2016“…Later, the optimisation algorithm will be tested and verified using test problems from literature. …”
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The Bacterial Foraging Optimisation Algorithm using Prototype Selection and Prototype Generation for Data Classification
Published 2020“…Technically, BFOA has been applied as supplementary algorithm for optimizing weight, parameters for other classifier algorithms and selecting optimised features for other classifiers. …”
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Multi-Objective Discrete Particle Swarm Optimisation Algorithm for Integrated Assembly Sequence Planning and Assembly Line Balancing
Published 2016“…A computational experiment with 51 test problems at different difficulty levels was used to test the multi-objective discrete particle swarm optimisation performance compared with the existing algorithms. …”
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Enhancing harmony search parameters based on step and linear function for bus driver scheduling and rostering problems
Published 2018“…Optimization is a major challenge in numerous practical world problems.According to the “No Free Lunch (NFL)” theorem,there is no existing single optimizer algorithm that is able to resolve all issues in an effective and efficient manner.It is varied and need to be solved according to the specific capabilities inherent to certain algorithms making it hard to foresee the algorithm that is best suited for each problem.As a result,the heuristic technique is adopted for this research as it has been identified as a potentially suitable algorithm.Alternative heuristic algorithms are also suggested to obtain optimal solutions with reasonable computational effort.However,the heuristic approach failed to produce a solution that nears optimum when the complexity of a problem increases;therefore a type of nature-inspired algorithm known as meta-euristics which utilises an intelligent searching mechanism over a population is considered and consequently used.The meta-heuristic approach is widely used to substitute heuristic terms and is broadly applied to address problems with regards to driver scheduling.However,this meta-heuristic technique is still unable to address the fairness issue in the scheduling and rostering problems.Hence,this research proposes a strategy to adopt an amendment of the harmony search algorithm in order to address the fairness issue which in turn will escalate the level of fairness in driver scheduling and rostering.The harmony search algorithm is classified as a meta-heuristics algorithm that is capable of solving hard and combinatorial or discrete optimisation problems.In this respect,the three main operators in harmony search,namely the Harmony Memory Consideration Rate (HMCR),Pitch Adjustment Rate (PAR) and Bandwidth (BW) play a vital role in balancing local exploitation and global exploration.These parameters influence the overall performance of the HS algorithm,and therefore it is crucial to fine-tune them. …”
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Sensitivity analysis of GA parameters for ECED problem
Published 2023“…Besides the conventional method by using the Lagrange Multiplier several evolutionary computation techniques such as Genetic Algorithm, Particle Swarm Optimisation, Ant Colony and Differential Evolution have been gaining popularity in solving general economic dispatch problems due to their desirable characteristics such as non-gradient dependent and ability to search for global optima. …”
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Manufacturing process planning optimisation in reconfigurable multiple parts flow lines
Published 2008“…Findings: The results indicate that the two genetic algorithms are able to converge to optimal solutions in reasonable time. …”
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Adapting And Hybridising Harmony Search With Metaheuristic Components For University Course Timetabling
Published 2010“…The major thrust of this algorithm lies in its ability to integrate the key components of populationbased methods and local search-based methods in the same optimisation model. …”
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