Based on the queuing theory, a nonlinear optimization model is proposed in this paper. A novel transformation of optimization variables is devised and the constraints are properly combined so as to make this model int...Based on the queuing theory, a nonlinear optimization model is proposed in this paper. A novel transformation of optimization variables is devised and the constraints are properly combined so as to make this model into a convex one, from which the Lagrangian function and the KKT conditions are derived. The interiorpoint method for convex optimization is presented here as a computationally efficient tool. Finally, this model is evaluated on a real example, from which such conclusions are drawn that the optimum result can ensure the full utilization of machines and the least amount of WIP in manufacturing systems; the interior-point method for convex optimization needs fewer iterations with significant computational savings. It appears that many non-linear ootimization oroblems in the industrial engineering field would be amenable to this method of solution.展开更多
The service quality of a workstation depends mainly on its service load, ifnot taking into account all kinds of devices' break-downs. In this article, an optimization modelwith inequality constraints is proposed, ...The service quality of a workstation depends mainly on its service load, ifnot taking into account all kinds of devices' break-downs. In this article, an optimization modelwith inequality constraints is proposed, which aims to minimize the service load. A noveltransformation of optimization variables is also devised and the constraints are properly combinedso as to make this model into a convex one, whose corresponding Lagrange function and the KKTconditions are established afterwards. The interior-point method for convex optimization ispresented here as an efficient computation tool. Finally, this model is evaluated by a real example,from which conclusions are reached that the interior-point method possesses advantages such asfaster convergeoce and fewer iterations and it is possible to make complicated nonlinearoptimization problems exhibit convexity so as to obtain the optimum.展开更多
On the basis of the queuing theory, a nonlinear optimal load allocation model is proposed. A novel transformafion method for the optimization variables is also presented, and the constraints are properly combined so a...On the basis of the queuing theory, a nonlinear optimal load allocation model is proposed. A novel transformafion method for the optimization variables is also presented, and the constraints are properly combined so as to make this model convex. The interior-point method for convex optimization is presented as an efficient computational tool. Finally, this model is evaluated by a real example,from which the following conclusions are drawn： the optimum result can ensure the full utilization of machines and the smallest amount of WIP （work-in-progress） in queuing systems; the interior-point method needs a few iterations with significant computational savings; other performance measures of queuing systems can also be optimized in a similar way.展开更多
Based on queuing theory, a nonlinear optimization model is proposed in this paper, which has the service load as its objective function and includes three inequality constraints of Work In Progress （WIP）. A novel tr...Based on queuing theory, a nonlinear optimization model is proposed in this paper, which has the service load as its objective function and includes three inequality constraints of Work In Progress （WIP）. A novel transformation of optimization variables is also devised and the constraints are properly combined so as to make this model into a convex one from which the Lagrangian function and the Karurh Kuhn Tucker （KKT） conditions are derived. The interior-point method for convex optimization is presented here as a computationaUy efficient tool. Finally, this model is evaluated on a real example, from which such conclusions are reached that the optimum result can ensure the full utilization of machines and the least amount of WIP in manufacturing systems; the interior-point method needs fewer iterations with significant computational savings and it is possible to make nonlinear and complicated optimization problems convexified so as to obtain the optimum.展开更多
Production planning is the foremost task for manufacturing firms to deal with, especially adopting Flexible Manufacturing System (FMS) as the manufacturing strategy for production seeking an optimal balance between pr...Production planning is the foremost task for manufacturing firms to deal with, especially adopting Flexible Manufacturing System (FMS) as the manufacturing strategy for production seeking an optimal balance between productivity-flexibility requirements. Production planning in FMS provides a solution to problems regarding part type selection: machine grouping, production ratio, resource allocation and loading problem. These problems need to be solved optimally for maximum utilization of resources. Optimal solution to these problems has been a focus of attention in production and manufacturing, industrial and academic research since a number of decades. Evolution of new optimization techniques, software, technology, machines and computer languages provides the scope of a better optimal solution to the existing problems. Thus there remains a need of research to solve the problem with latest tools and techniques for higher optimal use of available resources. As an objective, the researchers need to reduce the computational time and cost, complexity of the problem, solution approach viz. general or customized, better user friendly communication with machine, higher freedom to select the desired objective(s) type(s) for optimal solution to the problem. As an approach to the solution to the problem, a researcher first needs to go for an exhaustive literature review, where the researcher needs to find the research gaps, compare and analyze the tools and techniques used, number of objectives considered for optimization and need, and scope of research for the research problem. The present study is a review paper analyzing the research gaps, approach and techniques used, scope of new optimization techniques or any other research, objectives considered and validation approaches for loading problems of production planning in FMS.展开更多
以带有半主动复合储能系统构型的纯电动客车作为研究对象,提出了一种以最小电池耗能及电池功率变化作为目标函数的凸优化方法。在中国哈尔滨城市公交道路工况的基础上,对所提优化方法与基于规则的功率分配策略进行能效及电池功率变化的...以带有半主动复合储能系统构型的纯电动客车作为研究对象,提出了一种以最小电池耗能及电池功率变化作为目标函数的凸优化方法。在中国哈尔滨城市公交道路工况的基础上,对所提优化方法与基于规则的功率分配策略进行能效及电池功率变化的对比分析。仿真结果表明,在中国哈尔滨城市公交道路工况条件下,采用所提凸优化功率分配策略,电池及超级电容的综合能效分别为93.46%和98.81%,电池功率的均方差为5.3153 k W,较之基于规则的功率分配策略,电池及超级电容的综合能效分别提高了0.74%和0.26%,电池功率均方差降低了46.91%。基于此功率优化分配方法能够有效的改善电动汽车的运行特性。展开更多
文摘Based on the queuing theory, a nonlinear optimization model is proposed in this paper. A novel transformation of optimization variables is devised and the constraints are properly combined so as to make this model into a convex one, from which the Lagrangian function and the KKT conditions are derived. The interiorpoint method for convex optimization is presented here as a computationally efficient tool. Finally, this model is evaluated on a real example, from which such conclusions are drawn that the optimum result can ensure the full utilization of machines and the least amount of WIP in manufacturing systems; the interior-point method for convex optimization needs fewer iterations with significant computational savings. It appears that many non-linear ootimization oroblems in the industrial engineering field would be amenable to this method of solution.
文摘The service quality of a workstation depends mainly on its service load, ifnot taking into account all kinds of devices' break-downs. In this article, an optimization modelwith inequality constraints is proposed, which aims to minimize the service load. A noveltransformation of optimization variables is also devised and the constraints are properly combinedso as to make this model into a convex one, whose corresponding Lagrange function and the KKTconditions are established afterwards. The interior-point method for convex optimization ispresented here as an efficient computation tool. Finally, this model is evaluated by a real example,from which conclusions are reached that the interior-point method possesses advantages such asfaster convergeoce and fewer iterations and it is possible to make complicated nonlinearoptimization problems exhibit convexity so as to obtain the optimum.
文摘On the basis of the queuing theory, a nonlinear optimal load allocation model is proposed. A novel transformafion method for the optimization variables is also presented, and the constraints are properly combined so as to make this model convex. The interior-point method for convex optimization is presented as an efficient computational tool. Finally, this model is evaluated by a real example,from which the following conclusions are drawn： the optimum result can ensure the full utilization of machines and the smallest amount of WIP （work-in-progress） in queuing systems; the interior-point method needs a few iterations with significant computational savings; other performance measures of queuing systems can also be optimized in a similar way.
文摘Based on queuing theory, a nonlinear optimization model is proposed in this paper, which has the service load as its objective function and includes three inequality constraints of Work In Progress （WIP）. A novel transformation of optimization variables is also devised and the constraints are properly combined so as to make this model into a convex one from which the Lagrangian function and the Karurh Kuhn Tucker （KKT） conditions are derived. The interior-point method for convex optimization is presented here as a computationaUy efficient tool. Finally, this model is evaluated on a real example, from which such conclusions are reached that the optimum result can ensure the full utilization of machines and the least amount of WIP in manufacturing systems; the interior-point method needs fewer iterations with significant computational savings and it is possible to make nonlinear and complicated optimization problems convexified so as to obtain the optimum.
文摘Production planning is the foremost task for manufacturing firms to deal with, especially adopting Flexible Manufacturing System (FMS) as the manufacturing strategy for production seeking an optimal balance between productivity-flexibility requirements. Production planning in FMS provides a solution to problems regarding part type selection: machine grouping, production ratio, resource allocation and loading problem. These problems need to be solved optimally for maximum utilization of resources. Optimal solution to these problems has been a focus of attention in production and manufacturing, industrial and academic research since a number of decades. Evolution of new optimization techniques, software, technology, machines and computer languages provides the scope of a better optimal solution to the existing problems. Thus there remains a need of research to solve the problem with latest tools and techniques for higher optimal use of available resources. As an objective, the researchers need to reduce the computational time and cost, complexity of the problem, solution approach viz. general or customized, better user friendly communication with machine, higher freedom to select the desired objective(s) type(s) for optimal solution to the problem. As an approach to the solution to the problem, a researcher first needs to go for an exhaustive literature review, where the researcher needs to find the research gaps, compare and analyze the tools and techniques used, number of objectives considered for optimization and need, and scope of research for the research problem. The present study is a review paper analyzing the research gaps, approach and techniques used, scope of new optimization techniques or any other research, objectives considered and validation approaches for loading problems of production planning in FMS.
文摘以带有半主动复合储能系统构型的纯电动客车作为研究对象,提出了一种以最小电池耗能及电池功率变化作为目标函数的凸优化方法。在中国哈尔滨城市公交道路工况的基础上,对所提优化方法与基于规则的功率分配策略进行能效及电池功率变化的对比分析。仿真结果表明,在中国哈尔滨城市公交道路工况条件下,采用所提凸优化功率分配策略,电池及超级电容的综合能效分别为93.46%和98.81%,电池功率的均方差为5.3153 k W,较之基于规则的功率分配策略,电池及超级电容的综合能效分别提高了0.74%和0.26%,电池功率均方差降低了46.91%。基于此功率优化分配方法能够有效的改善电动汽车的运行特性。
