Search Results - (( problem solving maximization algorithm ) OR ( java application optimization algorithm ))

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  1. 1
    Shuffled Frog Leaping Algorithm (SFLA) for solving profit based unit commitment problem / Nurul Izzati Mohd Hanapiah

    Shuffled Frog Leaping Algorithm (SFLA) for solving profit based unit commitment problem / Nurul Izzati Mohd Hanapiah by Mohd Hanapiah, Nurul Izzati

    Published 2016
    “…This thesis presents the Shuffled Frog Leaping Algorithm (SFLA) technique is used to solve the Profit Based Unit Commitment Problem (PBUCP). …”
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  2. 2
    Higher desirability in solving multiple response optimization problems with committee machine

    Higher desirability in solving multiple response optimization problems with committee machine by Golestaneh, Seyed Jafar, Ismail, Napsiah, Mohd Ariffin, Mohd Khairol Anuar, Tang, Sai Hong, Naeini, Hassan Moslemi, Maghsoudi, Ali Asghar, Firoozi, Zahra

    Published 2014
    “…Then, another GA specifies the final solution with object maximizing the global desirability. This algorithm was implemented on five case studies and the results represent the algorithm can get higher global desirability by repeating the runs and economic run number (ERN) depends on the MRO problem objective. …”
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  3. 3
    Using artificial intelligence search in solving the camera placement problem

    Using artificial intelligence search in solving the camera placement problem by Altahir, A.A., Asirvadam, V.S., Hamid, N.H.B., Sebastian, P.

    Published 2022
    “…Two case studies are used to evaluate those algorithms, and the camera placement problem is formulated as a coverage maximization problem. …”
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  4. 4
    Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage

    Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage by Nor Azlina, Ab. Aziz, Zuwairie, Ibrahim, Kamarulzaman, Ab Aziz, Nor Hidayati, Abdul Aziz

    Published 2019
    “…Many metaheuristics algorithms had been applied to solve this problem. Here, SKF is tested over several WSN and found to be able to perform better than particle swarm optimization (PSO) and genetic algorithm (GA) in improving WSN coverage.…”
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  5. 5
    Hybrid tabu search – strawberry algorithm for multidimensional knapsack problem

    Hybrid tabu search – strawberry algorithm for multidimensional knapsack problem by Wong, Jerng Foong

    Published 2022
    “…In 2011, a new metaheuristic known as Strawberry algorithm (SBA) was initiated. Since then, it has been vastly applied to solve engineering problems. …”
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  6. 6
    New fundamental theory in solving the royalty payment problem / Wan Noor Afifah Wan Ahmad and Suliadi Firdaus Sufahani

    New fundamental theory in solving the royalty payment problem / Wan Noor Afifah Wan Ahmad and Suliadi Firdaus Sufahani by Wan Ahmad, Wan Noor Afifah, Sufahani, Suliadi Firdaus

    Published 2020
    “…However, solving the problem, this project has to clarify a few constraints. …”
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  7. 7
    Multi-objective constrained algorithm (MCA) and non-dominated sorting genetic algorithm (NSGA-ii) for solving multi-objective crop planning problem

    Multi-objective constrained algorithm (MCA) and non-dominated sorting genetic algorithm (NSGA-ii) for solving multi-objective crop planning problem by Jarin, Sams, Khatun, Mst Khaleda, Shafie, Amir Akramin

    Published 2016
    “…In this paper, we formulate a crop planning problem as a multiobjective optimization model and try to solve two different versions of the problem using two different optimization algorithms MCA and NSGA. …”
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  8. 8
    Optimization of mycelium growth using genetic algorithm for multi-objective functions

    Optimization of mycelium growth using genetic algorithm for multi-objective functions by Muhamad Faiz, Abu Bakar

    Published 2019
    “…However, for optimizing mycelium growth, there are more than one function that needs to be calculated and solved, making this problem as a multi-objective optimization problem. …”
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  9. 9
    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model

    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…Meanwhile, Kmeans clustering algorithm has also been reported has widely known for solving most unsupervised classification problems. …”
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  10. 10
    A Simulated Annealing Approach to Solve Fuzzy Multi-Objective Linear Model for Supplier Selection in a Supply Chain

    A Simulated Annealing Approach to Solve Fuzzy Multi-Objective Linear Model for Supplier Selection in a Supply Chain by Parthiban, P, Dominic P, Dhanapal Durai, dhanalakshmi, p

    Published 2010
    “…Finally the problem is solved by using simulated annealing algorithm to enable the decision-maker to select the right suppliers and allocate their quota in order to minimize the cost, maximize the quality level and again maximize the service level.…”
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  11. 11
    A Novel Discrete Filled Function Algorithm in Solving Discrete Optimization Problems (S/O: 12408)

    A Novel Discrete Filled Function Algorithm in Solving Discrete Optimization Problems (S/O: 12408) by Woon, Siew Fang, Karim, Sharmila, Mohamad, Mohd Saiful Adli

    Published 2016
    “…Numerical results suggest that the proposed algorithm is efficient in solving large scale complex discrete optimization problems, thus could be extended into solving real life application mixed discrete optimization problem in the future…”
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    Monograph
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  12. 12
    An implementation of differential evolution algorithm for a single product and single period multi-echelon supply chain network model

    An implementation of differential evolution algorithm for a single product and single period multi-echelon supply chain network model by Ayda, Emdadian, Ponnambalam, S. G., Kanagaraj, G.

    Published 2018
    “…In this paper, five variants of Differential Evolution (DE) algorithms are proposed to solve the multi-echelon supply chain network optimization problem. …”
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  13. 13
    Hybrid of firefly algorithm and pattern search for solving optimization problems

    Hybrid of firefly algorithm and pattern search for solving optimization problems by Wahid, Fazli, Ghazali, Rozaida

    Published 2018
    “…Firefly algorithm (FA) is a newly introduced meta-heuristic, nature-inspired, stochastic algorithm for solving various types of optimization problems. …”
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  14. 14
    Development of optimization Alghorithm for uncertain non-linear dynamical system

    Development of optimization Alghorithm for uncertain non-linear dynamical system by Abdul Aziz, Mohd. Ismail, Yaacob, Nazeeruddin, Mohd. Said, Norfarizan, Hamzah, Nor Hazadura

    Published 2004
    “…This study succeeded in overcoming the problem of slow convergence and with the modifications, the new algorithms become more efficient in solving the optimal control problems.…”
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  15. 15
    Solving an application of university course timetabling problem by using genetic algorithm

    Solving an application of university course timetabling problem by using genetic algorithm by Norhana, Shaibatul Khadri

    Published 2022
    “…Among the approaches, genetic algorithm (GA), constructed based on Darwin's theory of evolution, becomes the renowned approach to solve various types of timetabling problems. …”
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  16. 16
    Optimization of blood vessel detection in retina images using multithreading and native code for portable devices

    Optimization of blood vessel detection in retina images using multithreading and native code for portable devices by Tran, Duc Ngoc, Hussin, Fawnizu Azmadi, Yusoff, Mohd Zuki

    Published 2013
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  17. 17
    Mathematical models and optimization algorithms for low-carbon Location-Inventory-Routing Problem with uncertainty

    Mathematical models and optimization algorithms for low-carbon Location-Inventory-Routing Problem with uncertainty by Liu, Lihua

    Published 2024
    “…Further more, an improved non-dominated sorting genetic algorithm with an elite strategy II (IMNSGA-II) has been developed to solve the two bi-objective models, surpassing existing literature’s algorithms such as Pareto Envelope-based Selection Algorithm II (PESA-II) and NSGA-II. …”
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  18. 18
    Performance evaluation of real-time multiprocessor scheduling algorithms

    Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

    Published 2016
    “…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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  19. 19
    Incorporating genetic algorithm into simulated annealing based redistricting

    Incorporating genetic algorithm into simulated annealing based redistricting by Sim, Kwan Hua.

    Published 2002
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  20. 20
    A new approach for optimum DG placement and sizing based on voltage stability maximization and minimization of power losses

    A new approach for optimum DG placement and sizing based on voltage stability maximization and minimization of power losses by Aman, M.M., Jasmon, G.B., Bakar, A.H.A., Mokhlis, Hazlie

    Published 2013
    “…Particle Swarm Optimization (PSO) algorithm is used in this paper to solve the multi-objective problem. …”
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