The order-of-addition experiments are widely used in many fields,including food and industrial production,but the relative research under prior constraints is limited.The purpose of this paper is to select an optimal ...The order-of-addition experiments are widely used in many fields,including food and industrial production,but the relative research under prior constraints is limited.The purpose of this paper is to select an optimal sequence under the restriction that component i is added before component j,while it is unachievable to compare all sequences when the number of components m is large.To achieve this,a constrained PWO model is first provided,and then the D-optimal designs for order-of addition experiments with minimal-points via the modified threshold accepting algorithm is established.The effectiveness of the proposed method is demonstrated through a job scheduling problem with a prior constraint for teaching cases.展开更多
基金supported by National Natural Science Foundation of China(Grant Nos.11971204,12271270)Natural Science Foundation of Jiangsu Province of China(Grant No.BK20200108)the Zhongwu Youth Innovative Talent Program of Jiangsu University of Technology and the Third Level Training Object of the Sixth“333 Project”in Jiangsu Province。
文摘The order-of-addition experiments are widely used in many fields,including food and industrial production,but the relative research under prior constraints is limited.The purpose of this paper is to select an optimal sequence under the restriction that component i is added before component j,while it is unachievable to compare all sequences when the number of components m is large.To achieve this,a constrained PWO model is first provided,and then the D-optimal designs for order-of addition experiments with minimal-points via the modified threshold accepting algorithm is established.The effectiveness of the proposed method is demonstrated through a job scheduling problem with a prior constraint for teaching cases.
基金国家自然科学基金联合基金项目(U21A20485)浙江省高等教育“十四五”本科教育教学改革项目(jg20220019)+3 种基金浙江省产学合作协同育人项目(202018)浙江大学2023年度本科教学创新实践项目重点项目(202309)浙江省基础公益研究计划项目(LGG22F030008)浙江大学第一批AI For Education系列实证教学研究项目(202402)。
