An improved genetic algorithm（IGA） based on a novel selection strategy to handle nonlinear programming problems is proposed.Each individual in selection process is represented as a three-dimensional feature vector w...An improved genetic algorithm（IGA） based on a novel selection strategy to handle nonlinear programming problems is proposed.Each individual in selection process is represented as a three-dimensional feature vector which is composed of objective function value,the degree of constraints violations and the number of constraints violations.It is easy to distinguish excellent individuals from general individuals by using an individuals＇ feature vector.Additionally,a local search（LS） process is incorporated into selection operation so as to find feasible solutions located in the neighboring areas of some infeasible solutions.The combination of IGA and LS should offer the advantage of both the quality of solutions and diversity of solutions.Experimental results over a set of benchmark problems demonstrate that IGA has better performance than other algorithms.展开更多
A quadratic bilevel programming problem is transformed into a single level complementarity slackness problem by applying Karush-Kuhn-Tucker（KKT） conditions.To cope with the complementarity constraints,a binary encod...A quadratic bilevel programming problem is transformed into a single level complementarity slackness problem by applying Karush-Kuhn-Tucker（KKT） conditions.To cope with the complementarity constraints,a binary encoding scheme is adopted for KKT multipliers,and then the complementarity slackness problem is simplified to successive quadratic programming problems,which can be solved by many algorithms available.Based on 0-1 binary encoding,an orthogonal genetic algorithm,in which the orthogonal experimental design with both two-level orthogonal array and factor analysis is used as crossover operator,is proposed.Numerical experiments on 10 benchmark examples show that the orthogonal genetic algorithm can find global optimal solutions of quadratic bilevel programming problems with high accuracy in a small number of iterations.展开更多
By applying Kuhn-Tucker condition the quadratic bilevel programming, a class of bilevel programming, is transformed into a single level programming problem, which can be simplified by some rule. So we can search the o...By applying Kuhn-Tucker condition the quadratic bilevel programming, a class of bilevel programming, is transformed into a single level programming problem, which can be simplified by some rule. So we can search the optimal solution in the feasible region, hence reduce greatly the searching space. Numerical experiments on several literature problems show that the new algorithm is both feasible and effective in practice.展开更多
“双碳”背景下,为促进能源绿色低碳转型,提出一种考虑绿证-碳交易联合机制与混合博弈的综合能源系统(integrated energy system, IES)低碳经济调度模型。首先,构建混合博弈双层模型,上层模型将系统运营商作为领导者,以最大化自身收益...“双碳”背景下,为促进能源绿色低碳转型,提出一种考虑绿证-碳交易联合机制与混合博弈的综合能源系统(integrated energy system, IES)低碳经济调度模型。首先,构建混合博弈双层模型,上层模型将系统运营商作为领导者,以最大化自身收益为目标制定购售能价格策略,下层模型将氢能多元利用的综合能源系统(hydrogen multienergy integrated energy system, HMIES)联盟作为跟随者,以联盟整体经济性最优为目标优化自身出力;然后,在HMIES联盟的合作博弈模型中引入绿证-碳联合交易机制,提高整体低碳经济性,同时结合合作博弈理论分析合作成立条件,并基于Shapley值法对合作剩余进行合理分配,实现联盟内部碳捕集电厂主体与新能源发电主体的协同互动;最后,采用遗传算法联合混合整数线性规划(genetic algorithm and the mixed integer linear programming, GAMILP)进行求解。通过算例仿真验证了所提策略的有效性,结果表明所提模型可有效降低碳排放、提升系统经济性。展开更多
基金supported by the National Natural Science Foundation of China (60632050)National Basic Research Program of Jiangsu Province University (08KJB520003)
文摘An improved genetic algorithm（IGA） based on a novel selection strategy to handle nonlinear programming problems is proposed.Each individual in selection process is represented as a three-dimensional feature vector which is composed of objective function value,the degree of constraints violations and the number of constraints violations.It is easy to distinguish excellent individuals from general individuals by using an individuals＇ feature vector.Additionally,a local search（LS） process is incorporated into selection operation so as to find feasible solutions located in the neighboring areas of some infeasible solutions.The combination of IGA and LS should offer the advantage of both the quality of solutions and diversity of solutions.Experimental results over a set of benchmark problems demonstrate that IGA has better performance than other algorithms.
基金supported by the National Natural Science Foundation of China (60873099)
文摘A quadratic bilevel programming problem is transformed into a single level complementarity slackness problem by applying Karush-Kuhn-Tucker（KKT） conditions.To cope with the complementarity constraints,a binary encoding scheme is adopted for KKT multipliers,and then the complementarity slackness problem is simplified to successive quadratic programming problems,which can be solved by many algorithms available.Based on 0-1 binary encoding,an orthogonal genetic algorithm,in which the orthogonal experimental design with both two-level orthogonal array and factor analysis is used as crossover operator,is proposed.Numerical experiments on 10 benchmark examples show that the orthogonal genetic algorithm can find global optimal solutions of quadratic bilevel programming problems with high accuracy in a small number of iterations.
基金Supported by the National Natural Science Foundation of China (70371032,60574071)
文摘By applying Kuhn-Tucker condition the quadratic bilevel programming, a class of bilevel programming, is transformed into a single level programming problem, which can be simplified by some rule. So we can search the optimal solution in the feasible region, hence reduce greatly the searching space. Numerical experiments on several literature problems show that the new algorithm is both feasible and effective in practice.
文摘“双碳”背景下,为促进能源绿色低碳转型,提出一种考虑绿证-碳交易联合机制与混合博弈的综合能源系统(integrated energy system, IES)低碳经济调度模型。首先,构建混合博弈双层模型,上层模型将系统运营商作为领导者,以最大化自身收益为目标制定购售能价格策略,下层模型将氢能多元利用的综合能源系统(hydrogen multienergy integrated energy system, HMIES)联盟作为跟随者,以联盟整体经济性最优为目标优化自身出力;然后,在HMIES联盟的合作博弈模型中引入绿证-碳联合交易机制,提高整体低碳经济性,同时结合合作博弈理论分析合作成立条件,并基于Shapley值法对合作剩余进行合理分配,实现联盟内部碳捕集电厂主体与新能源发电主体的协同互动;最后,采用遗传算法联合混合整数线性规划(genetic algorithm and the mixed integer linear programming, GAMILP)进行求解。通过算例仿真验证了所提策略的有效性,结果表明所提模型可有效降低碳排放、提升系统经济性。
