Developing a comprehensive service strategy to optimize customer satisfaction presents an ongoing challenge for effective facility provider.The essence of comprehensive systems is selecting the suitable service design...Developing a comprehensive service strategy to optimize customer satisfaction presents an ongoing challenge for effective facility provider.The essence of comprehensive systems is selecting the suitable service design,establishing an effective service delivery process,and building continuous improvement.This research analyzes a finite capacity service system incorporating several realistic customer-server dynamics:customer impatience,server’s partial breakdown,and threshold recovery policy.When the number of customers is more,the server is under pressure to increase the service rate to mitigate the service system’s load.Motivating from this fact,the concept of service pressure condition is also incorporated.For characterization,we evaluate state probabilities derived using the matrix-analytic method and henceforth several performance measures.To address the cost optimization problem involving the developed Chapman-Kolmogorov forward differential-difference equations and determine optimal operational parameters,we employ the recently devised cuckoo search(CS)optimization approach.A comparative analysis is performed with the semi-classical optimizer:quasi-Newton(QN)method,and metaheuristics technique:particle swarm optimization(PSO),to validate the efficacy of results.Lastly,several numerical illustrations are depicted in different tables and graphs to understand essential characteristics quickly.展开更多
近年来,深度强化学习在复杂控制任务中取得了令人瞩目的效果,然而由于超参数的高敏感性和收敛性难以保证等原因,严重影响了其对现实问题的适用性.元启发式算法作为一类模拟自然界客观规律的黑盒优化方法,虽然能够有效避免超参数的敏感性...近年来,深度强化学习在复杂控制任务中取得了令人瞩目的效果,然而由于超参数的高敏感性和收敛性难以保证等原因,严重影响了其对现实问题的适用性.元启发式算法作为一类模拟自然界客观规律的黑盒优化方法,虽然能够有效避免超参数的敏感性,但仍存在无法适应待优化参数量规模巨大和样本使用效率低等问题.针对以上问题,提出融合引力搜索的双延迟深度确定策略梯度方法(twin delayed deep deterministic policy gradient based on gravitational search algorithm,GSA-TD3).该方法融合两类算法的优势:一是凭借梯度优化的方式更新策略,获得更高的样本效率和更快的学习速度;二是将基于万有引力定律的种群更新方法引入到策略搜索过程中,使其具有更强的探索性和更好的稳定性.将GSA-TD3应用于一系列复杂控制任务中,实验表明,与前沿的同类深度强化学习方法相比,GSA-TD3在性能上具有显著的优势.展开更多
On December 7,2022,the Chinese government optimized the current epidemic prevention and control policy,and no longer adopted the zero-COVID policy and mandatory quarantine measures.Based on the above policy changes,th...On December 7,2022,the Chinese government optimized the current epidemic prevention and control policy,and no longer adopted the zero-COVID policy and mandatory quarantine measures.Based on the above policy changes,this paper establishes a compartment dynamics model considering age distribution,home isolation and vaccinations.Parameter estimation was performed using improved least squares and Nelder-Mead simplex algorithms combined with modified case data.Then,using the estimated parameter values to predict a second wave of the outbreak,the peak of severe cases will reach on 8 May 2023,the number of severe cases will reach 206,000.Next,it is proposed that with the extension of the effective time of antibodies obtained after infection,the peak of severe cases in the second wave of the epidemic will be delayed,and the final scale of the disease will be reduced.When the effectiveness of antibodies is 6 months,the severe cases of the second wave will peak on July 5,2023,the number of severe cases is 194,000.Finally,the importance of vaccination rates is demonstrated,when the vaccination rate of susceptible people under 60 years old reaches 98%,and the vaccination rate of susceptible people over 60 years old reaches 96%,the peak of severe cases in the second wave of the epidemic will be reached on 13 July 2023,when the number of severe cases is 166,000.展开更多
To avoid the effects of systemic financial risks caused by extreme fluctuations in housing price,the Chinese government has been exploring the most effective policies for regulating the housing market.Measuring the ef...To avoid the effects of systemic financial risks caused by extreme fluctuations in housing price,the Chinese government has been exploring the most effective policies for regulating the housing market.Measuring the effect of real estate regulation policies has been a challenge for present studies.This study innovatively employs big data technology to obtain Internet search data(ISD)and construct market concern index(MCI)of policy,and hedonic price theory to construct hedonic price index(HPI)based on building area,age,ring number,and other hedonic variables.Then,the impact of market concerns for restrictive policy,monetary policy,fiscal policy,security policy,and administrative supervision policy on housing prices is evaluated.Moreover,compared with the common housing price index,the hedonic price index considers the heterogeneity of houses and could better reflect the changes in housing prices caused by market supply and demand.The results indicate that(1)a long-term interaction relationship exists between housing prices and market concerns for policy(MCP);(2)market concerns for restrictive policy and administrative supervision policy effectively restrain rising housing prices while those for monetary and fiscal policy have the opposite effect.The results could serve as a useful reference for governments aiming to stabilize their real estate markets.展开更多
基金The third author(MD)extends his sincere thanks to the funding agency CSIR-UGC,India,for the financial support(SRF/NET 1081/(CSIR-UGC NET DEC.2018)).
文摘Developing a comprehensive service strategy to optimize customer satisfaction presents an ongoing challenge for effective facility provider.The essence of comprehensive systems is selecting the suitable service design,establishing an effective service delivery process,and building continuous improvement.This research analyzes a finite capacity service system incorporating several realistic customer-server dynamics:customer impatience,server’s partial breakdown,and threshold recovery policy.When the number of customers is more,the server is under pressure to increase the service rate to mitigate the service system’s load.Motivating from this fact,the concept of service pressure condition is also incorporated.For characterization,we evaluate state probabilities derived using the matrix-analytic method and henceforth several performance measures.To address the cost optimization problem involving the developed Chapman-Kolmogorov forward differential-difference equations and determine optimal operational parameters,we employ the recently devised cuckoo search(CS)optimization approach.A comparative analysis is performed with the semi-classical optimizer:quasi-Newton(QN)method,and metaheuristics technique:particle swarm optimization(PSO),to validate the efficacy of results.Lastly,several numerical illustrations are depicted in different tables and graphs to understand essential characteristics quickly.
文摘近年来,深度强化学习在复杂控制任务中取得了令人瞩目的效果,然而由于超参数的高敏感性和收敛性难以保证等原因,严重影响了其对现实问题的适用性.元启发式算法作为一类模拟自然界客观规律的黑盒优化方法,虽然能够有效避免超参数的敏感性,但仍存在无法适应待优化参数量规模巨大和样本使用效率低等问题.针对以上问题,提出融合引力搜索的双延迟深度确定策略梯度方法(twin delayed deep deterministic policy gradient based on gravitational search algorithm,GSA-TD3).该方法融合两类算法的优势:一是凭借梯度优化的方式更新策略,获得更高的样本效率和更快的学习速度;二是将基于万有引力定律的种群更新方法引入到策略搜索过程中,使其具有更强的探索性和更好的稳定性.将GSA-TD3应用于一系列复杂控制任务中,实验表明,与前沿的同类深度强化学习方法相比,GSA-TD3在性能上具有显著的优势.
基金supported by the National Natural Science Foundation of China(12022113 and 12271314)Henry Fok Foundation for Young Teachers(171002)Outstanding Young Talents Support Plan of Shanxi Province.
文摘On December 7,2022,the Chinese government optimized the current epidemic prevention and control policy,and no longer adopted the zero-COVID policy and mandatory quarantine measures.Based on the above policy changes,this paper establishes a compartment dynamics model considering age distribution,home isolation and vaccinations.Parameter estimation was performed using improved least squares and Nelder-Mead simplex algorithms combined with modified case data.Then,using the estimated parameter values to predict a second wave of the outbreak,the peak of severe cases will reach on 8 May 2023,the number of severe cases will reach 206,000.Next,it is proposed that with the extension of the effective time of antibodies obtained after infection,the peak of severe cases in the second wave of the epidemic will be delayed,and the final scale of the disease will be reduced.When the effectiveness of antibodies is 6 months,the severe cases of the second wave will peak on July 5,2023,the number of severe cases is 194,000.Finally,the importance of vaccination rates is demonstrated,when the vaccination rate of susceptible people under 60 years old reaches 98%,and the vaccination rate of susceptible people over 60 years old reaches 96%,the peak of severe cases in the second wave of the epidemic will be reached on 13 July 2023,when the number of severe cases is 166,000.
基金the National Natural Science Foundation of China(Nos.61703014 and 62073008).
文摘To avoid the effects of systemic financial risks caused by extreme fluctuations in housing price,the Chinese government has been exploring the most effective policies for regulating the housing market.Measuring the effect of real estate regulation policies has been a challenge for present studies.This study innovatively employs big data technology to obtain Internet search data(ISD)and construct market concern index(MCI)of policy,and hedonic price theory to construct hedonic price index(HPI)based on building area,age,ring number,and other hedonic variables.Then,the impact of market concerns for restrictive policy,monetary policy,fiscal policy,security policy,and administrative supervision policy on housing prices is evaluated.Moreover,compared with the common housing price index,the hedonic price index considers the heterogeneity of houses and could better reflect the changes in housing prices caused by market supply and demand.The results indicate that(1)a long-term interaction relationship exists between housing prices and market concerns for policy(MCP);(2)market concerns for restrictive policy and administrative supervision policy effectively restrain rising housing prices while those for monetary and fiscal policy have the opposite effect.The results could serve as a useful reference for governments aiming to stabilize their real estate markets.
