An integer linear bilevel programming problem is firstly transformed into a binary linear bilevel programming problem, and then converted into a single-level binary implicit programming. An orthogonal genetic algorith...An integer linear bilevel programming problem is firstly transformed into a binary linear bilevel programming problem, and then converted into a single-level binary implicit programming. An orthogonal genetic algorithm is developed for solving the binary linear implicit programming problem based on the orthogonal design. The orthogonal design with the factor analysis, an experimental design method is applied to the genetic algorithm to make the algorithm more robust, statistical y sound and quickly convergent. A crossover operator formed by the orthogonal array and the factor analysis is presented. First, this crossover operator can generate a smal but representative sample of points as offspring. After al of the better genes of these offspring are selected, a best combination among these offspring is then generated. The simulation results show the effectiveness of the proposed algorithm.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
In this paper they deal with the issue of specification and design of parallel communicatingprocesses. A trace-state based model is introduced to describe the behaviour of concurrent programs. They presenta formal sys...In this paper they deal with the issue of specification and design of parallel communicatingprocesses. A trace-state based model is introduced to describe the behaviour of concurrent programs. They presenta formal system based on that model to achieve hierarchical and modular development and verification methods. Anumber of refinement rules are used to decompose the specification into smaller ones and calculate program fromthe展开更多
[目的]针对《生物统计与试验设计》课程中数据处理复杂、学生参与度低等问题,开发一款轻量化教学工具,探索数字化教学改革的有效路径。[方法]基于Uniapp跨平台框架,结合豆包人工智能辅助开发技术,构建集成生物统计计算、试验设计模拟及...[目的]针对《生物统计与试验设计》课程中数据处理复杂、学生参与度低等问题,开发一款轻量化教学工具,探索数字化教学改革的有效路径。[方法]基于Uniapp跨平台框架,结合豆包人工智能辅助开发技术,构建集成生物统计计算、试验设计模拟及案例实操功能的微信小程序,在实验班(医动2211,n=23)与对照班(医动2212,n=26)开展对比教学实验,评估小程序的应用效果。[结果]教学实践数据显示:实验组学生完成数据处理任务的平均耗时较对照组缩短43.75%(45 min vs.80 min),课堂主动提问频次提升149%(2.64次/课vs.1.06次/课),理论知识考核成绩提高21.4%(85分vs.70分),实践操作成绩提升33.3%(40分vs.30分),差异均具有统计学意义(P<0.05);问卷调查表明,实验组学生课堂参与积极性达70%,显著高于对照组的35%。[结论]基于Uniapp和豆包AI的轻量化开发的微信小程序,显著提升了学生的理论理解深度与实践能力,为职业院校专业课程的数字化转型提供了可复制的解决方案。未来可进一步优化小程序功能,深化工具与教学场景的融合。展开更多
基金supported by the Fundamental Research Funds for the Central Universities(K50511700004)the Natural Science Basic Research Plan in Shaanxi Province of China(2013JM1022)
文摘An integer linear bilevel programming problem is firstly transformed into a binary linear bilevel programming problem, and then converted into a single-level binary implicit programming. An orthogonal genetic algorithm is developed for solving the binary linear implicit programming problem based on the orthogonal design. The orthogonal design with the factor analysis, an experimental design method is applied to the genetic algorithm to make the algorithm more robust, statistical y sound and quickly convergent. A crossover operator formed by the orthogonal array and the factor analysis is presented. First, this crossover operator can generate a smal but representative sample of points as offspring. After al of the better genes of these offspring are selected, a best combination among these offspring is then generated. The simulation results show the effectiveness of the proposed algorithm.
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ESPRIT Basic Research ProCoS project 3104 and 7071
文摘In this paper they deal with the issue of specification and design of parallel communicatingprocesses. A trace-state based model is introduced to describe the behaviour of concurrent programs. They presenta formal system based on that model to achieve hierarchical and modular development and verification methods. Anumber of refinement rules are used to decompose the specification into smaller ones and calculate program fromthe
文摘[目的]针对《生物统计与试验设计》课程中数据处理复杂、学生参与度低等问题,开发一款轻量化教学工具,探索数字化教学改革的有效路径。[方法]基于Uniapp跨平台框架,结合豆包人工智能辅助开发技术,构建集成生物统计计算、试验设计模拟及案例实操功能的微信小程序,在实验班(医动2211,n=23)与对照班(医动2212,n=26)开展对比教学实验,评估小程序的应用效果。[结果]教学实践数据显示:实验组学生完成数据处理任务的平均耗时较对照组缩短43.75%(45 min vs.80 min),课堂主动提问频次提升149%(2.64次/课vs.1.06次/课),理论知识考核成绩提高21.4%(85分vs.70分),实践操作成绩提升33.3%(40分vs.30分),差异均具有统计学意义(P<0.05);问卷调查表明,实验组学生课堂参与积极性达70%,显著高于对照组的35%。[结论]基于Uniapp和豆包AI的轻量化开发的微信小程序,显著提升了学生的理论理解深度与实践能力,为职业院校专业课程的数字化转型提供了可复制的解决方案。未来可进一步优化小程序功能,深化工具与教学场景的融合。
