With diversified requirements and varying manufacturing environments, the optimal production planning for a steel mill becomes more flexible and complicated. The flexibility provides operators with auxiliary requireme...With diversified requirements and varying manufacturing environments, the optimal production planning for a steel mill becomes more flexible and complicated. The flexibility provides operators with auxiliary requirements through an implementable integrated production planning. In this paper, a mixed-integer nonlinear programming(MINLP) model is proposed for the optimal planning that incorporates various manufacturing constraints and flexibility in a steel plate mill. Furthermore, two solution strategies are developed to overcome the weakness in solving the MINLP problem directly. The first one is to transform the original MINLP formulation to an approximate mixed integer linear programming using a classic linearization method. The second one is to decompose the original model using a branch-and-bound based iterative method. Computational experiments on various instances are presented in terms of the effectiveness and applicability. The result shows that the second method performs better in computational efforts and solution accuracy.展开更多
The key of production planning of refineries is to determine the production planning of units and blending schemes of blends in each period of the plan horizon,since they affect the effective utilization of components...The key of production planning of refineries is to determine the production planning of units and blending schemes of blends in each period of the plan horizon,since they affect the effective utilization of components of refineries and hence profits.The optimization is difficult,because of many complicated product production–consumption relationships in production processes,which are closely related to the running modes of the units.Additionally,the blending products,such as gasoline and diesel,may use multiple blending schemes for their production that increase the complexity of the problem.This paper models the production planning problem as a mixed integer nonlinear programming.Computational experiments for a refinery show the effectiveness of the model.The optimal results give the effective utilization of the self-produced components and increase of the profit.展开更多
Based on the study of supply chain(SC) and SC optimization in engineering projects, a mixed integer nonlinear programming(MINLP) optimization model is developed to minimize the total SC cost for international petroche...Based on the study of supply chain(SC) and SC optimization in engineering projects, a mixed integer nonlinear programming(MINLP) optimization model is developed to minimize the total SC cost for international petrochemical engineering projects. A steam cracking project is selected and analyzed, from which typical SC characteristics in international engineering projects in the area of petrochemical industry are summarized. The MINLP model is therefore developed and applied to projects with detailed data. The optimization results are analyzed and compared by the MINLP model, indicating that they are appropriate to SC management practice in engineering projects, and are consistent with the optimal priceeffective strategy in procurement. As a result, the model could provide useful guidance to SC optimization of international engineering projects in petrochemical industry, and improve SC management by selecting more reliable and qualified partner enterprises in SC for the project.展开更多
基金Supported in part by the National High Technology Research and Development Program of China(2012AA041701)the National Natural Science Foundation of China(61320106009) the 111 Project of China(B07031)
文摘With diversified requirements and varying manufacturing environments, the optimal production planning for a steel mill becomes more flexible and complicated. The flexibility provides operators with auxiliary requirements through an implementable integrated production planning. In this paper, a mixed-integer nonlinear programming(MINLP) model is proposed for the optimal planning that incorporates various manufacturing constraints and flexibility in a steel plate mill. Furthermore, two solution strategies are developed to overcome the weakness in solving the MINLP problem directly. The first one is to transform the original MINLP formulation to an approximate mixed integer linear programming using a classic linearization method. The second one is to decompose the original model using a branch-and-bound based iterative method. Computational experiments on various instances are presented in terms of the effectiveness and applicability. The result shows that the second method performs better in computational efforts and solution accuracy.
基金Supported by the State Key Laboratory of Synthetical Automation for Process Industries Fundamental Research Funds(2013ZCX02)
文摘The key of production planning of refineries is to determine the production planning of units and blending schemes of blends in each period of the plan horizon,since they affect the effective utilization of components of refineries and hence profits.The optimization is difficult,because of many complicated product production–consumption relationships in production processes,which are closely related to the running modes of the units.Additionally,the blending products,such as gasoline and diesel,may use multiple blending schemes for their production that increase the complexity of the problem.This paper models the production planning problem as a mixed integer nonlinear programming.Computational experiments for a refinery show the effectiveness of the model.The optimal results give the effective utilization of the self-produced components and increase of the profit.
文摘Based on the study of supply chain(SC) and SC optimization in engineering projects, a mixed integer nonlinear programming(MINLP) optimization model is developed to minimize the total SC cost for international petrochemical engineering projects. A steam cracking project is selected and analyzed, from which typical SC characteristics in international engineering projects in the area of petrochemical industry are summarized. The MINLP model is therefore developed and applied to projects with detailed data. The optimization results are analyzed and compared by the MINLP model, indicating that they are appropriate to SC management practice in engineering projects, and are consistent with the optimal priceeffective strategy in procurement. As a result, the model could provide useful guidance to SC optimization of international engineering projects in petrochemical industry, and improve SC management by selecting more reliable and qualified partner enterprises in SC for the project.
