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  1. Mohd Ismail Abd Aziz, Noryanti Nasir, Akbar Banitalebi
    MATEMATIKA, 2019;35(1):95-104.
    MyJurnal
    Successful oil palm plantation should have high profit, clean and environmental friendly. Since oil palm trees have a long life and it takes years to be fully grown, controlling the felling rate of the oil palm trees is a fundamental challenge. It needs to be addressed in order to maximize oil production. However, a good arrangement of the felling of the oil palm trees may also affect the amount of carbon absorption. The objec- tive of this study is to develop an optimal felling model of the oil palm plantation system taking into account both oil production and carbon absorption. The model facilitates in providing the optimal control of felling rate that results in maximizing both oil produc- tion and carbon absorption. With this aim, the model is formulated considering oil palm biomass, carbon absorption rate, oil production rate and the average prices of carbon and oil palm. A set of real data is used to estimate the parameters of the model and numerical simulation is conducted to highlight the application of the proposed model. The resulting parameter estimation that leads to an optimal control of felling rate problem is solved.
  2. Kashif Zaheer, Mohd Ismail Abd Aziz, Kashif, Amber Nehan, Syed Muhammad Murshid Raza
    MATEMATIKA, 2018;34(1):125-141.
    MyJurnal
    The selection criteria play an important role in the portfolio optimization
    using any ratio model. In this paper, the authors have considered the mean return as
    profit and variance of return as risk on the asset return as selection criteria, as the first
    stage to optimize the selected portfolio. Furthermore, the sharp ratio (SR) has been
    considered to be the optimization ratio model. In this regard, the historical data taken
    from Shanghai Stock Exchange (SSE) has been considered. A metaheuristic technique
    has been developed, with financial tool box available in MATLAB and the particle swarm
    optimization (PSO) algorithm. Hence, called as the hybrid particle swarm optimization
    (HPSO) or can also be called as financial tool box particle swarm optimization (FTBPSO).
    In this model, the budgets as constraint, where as two different models i.e. with
    and without short sale, have been considered. The obtained results have been compared
    with the existing literature and the proposed technique is found to be optimum and better
    in terms of profit.
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