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  1. 1
    Development of a multi-objective optimization model for transport and environment in a closed-loop automotive supply chain

    Development of a multi-objective optimization model for transport and environment in a closed-loop automotive supply chain by Sadrnia, Abdolhossein

    Published 2014
    “…In the last stage, an extended Gravitational Search Algorithm (GSA) as a parallel search algorithm and high convergence rate into high quality final solutions is used to solve the proposed mathematical model and to achieve the Pareto set of solution. …”
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  2. 2
    Multi-population Genetic Algorithm for Rich Vehicle Routing Problems

    Multi-population Genetic Algorithm for Rich Vehicle Routing Problems by Agany Manyiel, Joseph Mabor

    Published 2020
    “…MPGA-RVRP is applied in RVRP with three objectives:- total route distance, total route duration and total route cost. …”
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  3. 3
    Development of heuristic methods based on genetic algorithm (GA) for solving vehicle routing problem

    Development of heuristic methods based on genetic algorithm (GA) for solving vehicle routing problem by Ismail, Zuhaimy, Nurhadi, Irhamah, Zainuddin, Zaitul Marlizawati

    Published 2008
    “…Genetic Algorithm gives a pool of solutions rather than just one. …”
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    Monograph
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  4. 4
    Simulated Kalman Filter algorithms for solving optimization problems

    Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

    Published 2019
    “…Its optimality has inspired the development of a metaheuristic algorithm called Heuristic Kalman Algorithm (HKA) in 2009. …”
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  5. 5
    Dynamic Economic Dispatch For Power System

    Dynamic Economic Dispatch For Power System by Hussein, Saif Tahseen

    Published 2016
    “…The solution algorithm based on a constraint relaxation and period-by-period is developed and tested. …”
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  6. 6
    Hardware Software Partitioning Using Particle Swarm Optimization (PSO) In Image Processing Application

    Hardware Software Partitioning Using Particle Swarm Optimization (PSO) In Image Processing Application by Tan, Jia Zheng

    Published 2018
    “…In this project, car plate identification will be implemented in hardware-software partitioning by using PSO algorithm. The framework for hardware-software partitioning using PSO algorithm in MATLAB is developed. …”
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    Monograph
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  7. 7
    Development of cell formation algorithm and model for cellular manufacturing system

    Development of cell formation algorithm and model for cellular manufacturing system by Nouri, Hossein

    Published 2011
    “…In addition, one of the main challenges has been development of efficient algorithm for solving aforementioned model to find exact feasible optimal solution. …”
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  8. 8
    Implementation Of Hardware Software Partitioning In Embedded System

    Implementation Of Hardware Software Partitioning In Embedded System by Mohd Nor, Masyirah

    Published 2018
    “…As a conclusion, the hardware/software partitioning which is PSO and GA have been successfully develop in this project. The result shows that, the GA algorithm has better total area and total execution time but same cost compared to the PSO algorithm. …”
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    Monograph
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  9. 9
    An improved adaptive shuffled frog leaping algorithm to solve various non smooth economic dispatch problems in power system / Mohamad Helmi Muhamad Izham

    An improved adaptive shuffled frog leaping algorithm to solve various non smooth economic dispatch problems in power system / Mohamad Helmi Muhamad Izham by Muhamad Izham, Mohamad Helmi

    Published 2016
    “…This thesis discusses the solution of Economic Dispatch (ED) problems which is to minimize the total cost of generation in power system operation by using an improved adaptive shuffled frog leaping algorithm (lASFLA). …”
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  10. 10
    Hardware And Software Partitioning Using Genetic Algorithm In Image Processing Application

    Hardware And Software Partitioning Using Genetic Algorithm In Image Processing Application by Loo, Fang Hean

    Published 2018
    “…The framework for HW-SW Partitioning using Genetic Algorithm (GA) is developed in MATLAB. Total ten different combinations of GA parameters are used to test the developed framework. …”
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    Monograph
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  11. 11
    Development of an integrated scheduling model for handling equipment in automated port container terminals

    Development of an integrated scheduling model for handling equipment in automated port container terminals by Sadeghian, Syed Hamidreza

    Published 2014
    “…In addition, results proved that the modified meta-heuristic algorithm is able to find near optimal solutions and on average, the solutions found by the GA algorithm are only 0.2% worse than the optimal solutions and in the worst case in the test cases this difference is 2.3% which is acceptable. …”
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  12. 12
    Network reconfiguration and control for loss reduction using genetic algorithm

    Network reconfiguration and control for loss reduction using genetic algorithm by Jawad, Mohamed Hassan Izzaldeen

    Published 2010
    “…While in the 49-bus system the existing 7 capacitors are rearrange using Genetic Algorithm in obtaining minimal total power losses. …”
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  13. 13
    A greedy heuristics multiple criteria model for solving multi-landfill site selection and plant propagation algorithm for improving waste collection vehicle routing solutions

    A greedy heuristics multiple criteria model for solving multi-landfill site selection and plant propagation algorithm for improving waste collection vehicle routing solutions by Nur Azriati, Mat

    Published 2023
    “…The results revealed that a single landfill site (Candidate 4) was the best solution for the case-based scenario, with a 6.74% reduction in total distance travelled. …”
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  14. 14
    Simulated annealing for solving economic dispatch problem / Wan Khairulizuan Wan Ismail

    Simulated annealing for solving economic dispatch problem / Wan Khairulizuan Wan Ismail by Wan Ismail, Wan Khairulizuan

    Published 2010
    “…In the development of the algorithm, transmission losses are first discounted and they are subsequently incorporated in the algorithm through the use of the B-matrix loss formula. …”
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  15. 15
    A modified shuffled frog leaping algorithm and its application to short-term hydrothermal scheduling / Mohamad Khairul Hakimi Abdul Hady

    A modified shuffled frog leaping algorithm and its application to short-term hydrothermal scheduling / Mohamad Khairul Hakimi Abdul Hady by Abdul Hady, Mohamad Khairul Hakimi

    Published 2016
    “…This paper presents a modified shuffled frog leaping algorithm in order to accelerate the global search solution. …”
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  16. 16
    Parallel block methods for solving higher order ordinary differential equations directly

    Parallel block methods for solving higher order ordinary differential equations directly by Omar, Zurni

    Published 1999
    “…Hence, the development of parallel algorithms to suit these machines becomes essential. …”
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  17. 17
    Multi -Objective Economic Dispatch Using Evolutionary Programming

    Multi -Objective Economic Dispatch Using Evolutionary Programming by Noor Azlan Bin Adnan

    Published 2023
    “…Therefore, this project proposed an algorithm to minimize total cost and total losses simultaneously and find the best adjustment for this economic dispatch problems. …”
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  18. 18
    Variable Neighbourhood Search Algorithm for Vehicle Routing Problem with Backhaul

    Variable Neighbourhood Search Algorithm for Vehicle Routing Problem with Backhaul by Siaw Ying Doreen, Sek

    Published 2023
    “…The VNS algorithm is used to improve the obtained solutions in the improvement phase. …”
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  19. 19
    An Environmentally Energy Dispatch Using New Meta Heuristic Evolutionary Programming

    An Environmentally Energy Dispatch Using New Meta Heuristic Evolutionary Programming by Mohamad Ridzuan, Mohamad Radzi

    Published 2018
    “…Basically,one important issue in the power system network is to provide the optimal Economic Load Dispatch (ELD) solution in order to guarantee the sustainable consumer load demand.However,today ELD solution is essential to include together with the environmental aspect and known as Environmental Economic Load Dispatch (EELD).For that reason, many researchers continue in the development of new simulation tool specifically to overcome the EELD problems.Therefore,this study prepared an improved hybrid metaheuristic technique named as New Meta Heuristic Evolutionary Programming (NMEP) to provide the best possible solution in solving the identified single objective and multi objective functions for EELD solution.This new technique a merging cloning strategy that involved in an Artificial Immune System (AIS) algorithm into algorithm of Meta Heuristic Evolutionary Programming (Meta-EP).The development of NMEP technique is to minimize total cost,reduce the total emission during generator operation through the common formula in EELD and lowest total system loss.Besides that,all mentioned objective functions were also optimized together simultaneously that formulated using the weighted sum method before had been executed on the multi objective NMEP or called MONMEP.Both individual and multi objective NMEP techniques performance were verified among other two common heuristic methods known as AIS and Meta-EP techniques.In addition,the best possible solution defined using the aggregate function method.Through this method,the selection of the best MOEELD solution became effortless as compared with MO individually that required compare two or more objective function in one time manually.Among those three optimization techniques the lowest total aggregate values mostly resulted via the NMEP technique.Based upon that,the proposed technique is proving as the outstanding method compared with Meta-EP and AIS techniques in solving the EELD problem for both standard IEEE 26 bus and 57 bus systems.…”
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  20. 20
    Optimised Crossover Genetic Algorithms for Combinatorial Optimisation Problems

    Optimised Crossover Genetic Algorithms for Combinatorial Optimisation Problems by Nazif, Habibeh

    Published 2010
    “…A Genetic Algorithm is successful in generating near -optimal solutions if it is able to produce o®spring during crossover that is better than the parent solutions. …”
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