Balancing time,cost,and quality is crucial in intelligent manufacturing.However,finding the optimal value of production parameters is a challengingnon-deterministic polynomial(NP)-hard problem.In the actual production...Balancing time,cost,and quality is crucial in intelligent manufacturing.However,finding the optimal value of production parameters is a challengingnon-deterministic polynomial(NP)-hard problem.In the actual production process,the production process has the characteristics of multi-stage parallel.Therefore,aiming at the difficult problem of multi-stage nonlinear production process optimization,this paper proposes a workflow optimization algorithm based on virtualization and nonlinear production quality under time constraints(T-OVQT).The algorithm proposed in this paper first abstracts the actual production process into a virtual workflow model,which is divided into three layers:The bottom production process collection layer,the middle layer of service node partial order composition layer,and the high level of virtual node collection layer.Then,the virtual technology is used to reconstruct the node set and divide the task interval.The optimal solution is obtained through inverse iterative normalization and forward scheduling,and the global optimal solution is obtained by algorithm integration.Experimental results demonstrate that this algorithm better meets actual production requirements than the traditional minimum critical path(MCP)algorithm.展开更多
时间、生产质量和成本是加工制造中相互制约的重要参数,平衡此参数使制造工艺最优是一个NP(Non-deterministic polynomial)难题,对此出现了许多优秀的调度方法.然而这些方法的优化对象均为线性工艺,对于普遍存在的非线性工艺却无法调度...时间、生产质量和成本是加工制造中相互制约的重要参数,平衡此参数使制造工艺最优是一个NP(Non-deterministic polynomial)难题,对此出现了许多优秀的调度方法.然而这些方法的优化对象均为线性工艺,对于普遍存在的非线性工艺却无法调度优化.针对此不足,本文以非线性工艺为优化对象提出了三层虚拟工作流模型Three-VMG(Three-virtual model graph)及其优化算法Three-OVMG(Three-optimal virtual model graph).该模型和算法首先建立非线性工作流,采用虚拟技术寻找虚拟结点进行重构,将其改造为虚拟线性工作流;其次结合工艺特点对模型进行分段,采用逆向分层串归约来实现段内最优解,采用累积最优解来衔接各段间的值;最后根据优化结果自顶向下完成各层资源的优化调度.实验表明,该过程较传统时间最小化优化调度算法具有显著的优化效果,其性能及可操作性也能满足工程要求.展开更多
基金supported by Heilongjiang Provincial Natural Science Foundation of China(LH2021F030)。
文摘Balancing time,cost,and quality is crucial in intelligent manufacturing.However,finding the optimal value of production parameters is a challengingnon-deterministic polynomial(NP)-hard problem.In the actual production process,the production process has the characteristics of multi-stage parallel.Therefore,aiming at the difficult problem of multi-stage nonlinear production process optimization,this paper proposes a workflow optimization algorithm based on virtualization and nonlinear production quality under time constraints(T-OVQT).The algorithm proposed in this paper first abstracts the actual production process into a virtual workflow model,which is divided into three layers:The bottom production process collection layer,the middle layer of service node partial order composition layer,and the high level of virtual node collection layer.Then,the virtual technology is used to reconstruct the node set and divide the task interval.The optimal solution is obtained through inverse iterative normalization and forward scheduling,and the global optimal solution is obtained by algorithm integration.Experimental results demonstrate that this algorithm better meets actual production requirements than the traditional minimum critical path(MCP)algorithm.
文摘时间、生产质量和成本是加工制造中相互制约的重要参数,平衡此参数使制造工艺最优是一个NP(Non-deterministic polynomial)难题,对此出现了许多优秀的调度方法.然而这些方法的优化对象均为线性工艺,对于普遍存在的非线性工艺却无法调度优化.针对此不足,本文以非线性工艺为优化对象提出了三层虚拟工作流模型Three-VMG(Three-virtual model graph)及其优化算法Three-OVMG(Three-optimal virtual model graph).该模型和算法首先建立非线性工作流,采用虚拟技术寻找虚拟结点进行重构,将其改造为虚拟线性工作流;其次结合工艺特点对模型进行分段,采用逆向分层串归约来实现段内最优解,采用累积最优解来衔接各段间的值;最后根据优化结果自顶向下完成各层资源的优化调度.实验表明,该过程较传统时间最小化优化调度算法具有显著的优化效果,其性能及可操作性也能满足工程要求.
