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|Title:||Optimising petrochemical logistics||Authors:||Soh, Linda Xiao Yu.||Keywords:||DRNTU::Engineering::Maritime studies::Maritime management and business||Issue Date:||2010||Abstract:||This study presents a maritime collaboration with the petrochemical logistics that aims to research on the logistics optimization models to incorporate the petrochemical market knowledge and the identified literature gaps into the existing models to optimize logistics in an integrated petrochemical supply chain so as to enhance their core capabilities- integrated supply chain management. Based on relevant literature reviews, interviews were conducted in January 2010 with a ship chartering manager and with a process engineer of a petrochemical company to incorporate the market practices and norms into the optimization models. After the incorporations, sensitivity analysis and solutions report was generated to better understand how this model can be used to improve the optimization in the logistics area. From the results, several findings can be drawn from the model. Firstly, the temporary ship storage solution is feasible for application during a single period where there is a surge in demand. And secondly, the analysis shows that the smaller the vessel capacity, the higher the utilization rate of the storage capacities. This would suggest that the smaller vessel size provides flexibility to sudden surges in demands in a single period. The findings eventually lead the team to the conclusion that during a single period uncertainty, additional facilities of smaller capacity will aid in alleviating the shortage problems in the petrochemical logistics. Due to time and resource constraints, the models created are not able to provide an optimal answer because of the complexity of the model to be solved under linear programming and the nature of the Evolutionary Solver. The Evolutionary Solver though unable to provide optimized answers, it provides a good guide to the users. Furthermore, the 2 models are linked only by a derived voyage day, which confines the team to perform individual model analysis. For future development, our team suggests more researches can be done in the area on the mathematical aspect between the storage capacity and the production rate in multiple periods.||URI:||http://hdl.handle.net/10356/39029||Rights:||Nanyang Technological University||Fulltext Permission:||restricted||Fulltext Availability:||With Fulltext|
|Appears in Collections:||CEE Student Reports (FYP/IA/PA/PI)|
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