Steady-state non-dominated sorting genetic algorithm (SNSGA), a new form of multi-objective genetic
algorithm, is implemented by combining the steady-state idea in steady-state genetic algorithms (SSGA) and the
fitn...Steady-state non-dominated sorting genetic algorithm (SNSGA), a new form of multi-objective genetic
algorithm, is implemented by combining the steady-state idea in steady-state genetic algorithms (SSGA) and the
fitness assignment strategy of non-dominated sorting genetic algorithm (NSGA). The fitness assignment strategy is
improved and a new self-adjustment scheme of σshare is proposed. This algorithm is proved to be very efficient both
computationally and in terms of the quality of the Pareto fronts produced with five test problems including GA
difficult problem and GA deceptive one. Finally, SNSGA is introduced to solve multi-objective mixed integer linear programming (MILP) and mixed integer non-linear programming (MINLP) problems in process synthesis.展开更多
园区综合能源系统通过多能耦合互补和协同优化调度,可以显著提高能源利用率和促进可再生能源消纳,已成为用户侧满足多能供需的一种新的能源利用实现方式。以河北雄安新区某园区作为研究对象,设计了一种计及负荷供给可靠性的园区综合能...园区综合能源系统通过多能耦合互补和协同优化调度,可以显著提高能源利用率和促进可再生能源消纳,已成为用户侧满足多能供需的一种新的能源利用实现方式。以河北雄安新区某园区作为研究对象,设计了一种计及负荷供给可靠性的园区综合能源系统两阶段优化方法:第一阶段基于带有精英保留策略的二代非支配排序遗传算法(NSGA-Ⅱ),对园区能源站设备类型及容量进行优化,是一个多目标规划优化问题,其目的是实现经济成本和环境成本的协调优化;第二阶段是一个运行优化问题,针对上一阶段规划得到的多组帕累托前沿解,利用混合整数线性规划(mixed integer linear programming,MILP)分别优化求解各规划方案对应运行成本及负荷供给可靠性指标,结果作为确定系统最佳规划方案的重要参考。算例表明,所设计规划方法可以有效降低系统运行成本和保障负荷供给可靠性,对指导园区综合能源系统规划更具实用性。展开更多
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
文摘Steady-state non-dominated sorting genetic algorithm (SNSGA), a new form of multi-objective genetic
algorithm, is implemented by combining the steady-state idea in steady-state genetic algorithms (SSGA) and the
fitness assignment strategy of non-dominated sorting genetic algorithm (NSGA). The fitness assignment strategy is
improved and a new self-adjustment scheme of σshare is proposed. This algorithm is proved to be very efficient both
computationally and in terms of the quality of the Pareto fronts produced with five test problems including GA
difficult problem and GA deceptive one. Finally, SNSGA is introduced to solve multi-objective mixed integer linear programming (MILP) and mixed integer non-linear programming (MINLP) problems in process synthesis.
文摘园区综合能源系统通过多能耦合互补和协同优化调度,可以显著提高能源利用率和促进可再生能源消纳,已成为用户侧满足多能供需的一种新的能源利用实现方式。以河北雄安新区某园区作为研究对象,设计了一种计及负荷供给可靠性的园区综合能源系统两阶段优化方法:第一阶段基于带有精英保留策略的二代非支配排序遗传算法(NSGA-Ⅱ),对园区能源站设备类型及容量进行优化,是一个多目标规划优化问题,其目的是实现经济成本和环境成本的协调优化;第二阶段是一个运行优化问题,针对上一阶段规划得到的多组帕累托前沿解,利用混合整数线性规划(mixed integer linear programming,MILP)分别优化求解各规划方案对应运行成本及负荷供给可靠性指标,结果作为确定系统最佳规划方案的重要参考。算例表明,所设计规划方法可以有效降低系统运行成本和保障负荷供给可靠性,对指导园区综合能源系统规划更具实用性。
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.
