石墨采矿生产过程中最优产品组合决策的网络优化

K. S. M. Karunamuni, E. Ekanayake, Subodha Dharmapriya, A. Kulatunga
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引用次数: 0

摘要

目的针对石墨开采生产过程中生产过程复杂且子过程可选的商业石墨产品,建立一种新的通用数学模型,寻找最优产品组合。设计/方法/方法采用网络优化方法,对具有不同加工能力和成本的石墨原料、副产物和可销售产品进行优化配置,对复杂的石墨开采生产过程进行建模。在选定的石墨生产企业上对模型进行了验证,通过选择最优生产工艺确定了最优的石墨产品组合。此外,还进行了敏感性和情景分析,以适应不确定因素并促进进一步的管理决策。研究结果选定的石墨矿业公司每月开采约400公吨原料石墨,生产十种石墨产品。根据得到的最优解,该公司应只生产六种石墨产品,以使其总利润最大化。此外,研究还展示了如何基于最优解决方案揭示最优管理决策。原创性/价值本研究通过网络优化技术对复杂的石墨开采生产过程进行建模,对石墨制造业做出了重大贡献,该技术尚未在这个细节层面上得到解决。敏感性和情景分析支持进一步的管理决策。
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Network optimization for optimal product mix decisions in a graphite mining production process
PurposeThe purpose of this study is to develop a novel general mathematical model to find the optimal product mix of commercial graphite products, which has a complex production process with alternative sub-processes in the graphite mining production process.Design/methodology/approachThe network optimization was adopted to model the complex graphite mining production process through the optimal allocation of raw graphite, byproducts, and saleable products with comparable sub-processes, which has different processing capacities and costs. The model was tested on a selected graphite manufacturing company, and the optimal graphite product mix was determined through the selection of the optimal production process. In addition, sensitivity and scenario analyses were carried out to accommodate uncertainties and to facilitate further managerial decisions.FindingsThe selected graphite mining company mines approximately 400 metric tons of raw graphite per month to produce ten types of graphite products. According to the optimum solution obtained, the company should produce only six graphite products to maximize its total profit. In addition, the study demonstrated how to reveal optimum managerial decisions based on optimum solutions.Originality/valueThis study has made a significant contribution to the graphite manufacturing industry by modeling the complex graphite mining production process with a network optimization technique that has yet to be addressed at this level of detail. The sensitivity and scenario analyses support for further managerial decisions.
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