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Maximizing Crude Palm Oil Production in Malaysia: A Search for an Optimal Policy Using System Dynamics and Genetic Algorithm Approach

Palm oil industry in Malaysia is experiencing a stagnant crude palm oil (CPO) production and has been lagging as compared to Indonesia. This situation can jeopardize Malaysia’s position in world palm oil marker since Malaysia needed to secure its export revenue and fulfilling increasing demand of palm oil both locally and globally in the future. The factors that influence the CPO production are many. Among others are the scarcity of plantation area, labour shortage, and demand from palm-based biodiesel industry. This study presents an integrated of system dynamics (SD) and genetic algorithm (GA) (SD-GA) model to find the optimal policy to improve CPO production in Malaysian palm oil industry. SD offers the platform to evaluate and to test policy while GA facilitate the process of searching the best solutions to achieve the maximum CPO production in 2050. The proposed model has produced five optimal values for five policy variables namely average replanting rate, mechanization adoption rate, and biodiesel mandate in transportation, industrial and other sectors respectively. The best solution suggested that CPO replanting rate need to be increased to 251743.5 hectares per year to decrease the accumulation of ageing area by optimizing all these policy variables. This study is expected to help policy makers in designing related policies and drawing the road map towards improving CPO production in Malaysian palm oil industry.