摘要
为高效、稳定地求解预制构件生产过程中的时间-成本-碳排放目标均衡问题,提出一种基于子集模拟的优化算法。首先根据时间、成本和碳排放3个目标的重要程度,通过赋予权重系数的方式,构建多模式下预制构件生产目标均衡优化模型,并对模型决策变量进行转换处理,以实数编码的方式进行问题求解。其次,基于模型约束条件,为获得合理的初始种群,提出随机产生和马尔科夫链蒙特卡罗模拟方法(MCMCS)相结合的初始样本点生成方式。在子集模拟迭代过程中,为增加样本的多样性,采取均匀间隔取点的MCMCS,提高该方法在全局范围内的搜索能力。最后,通过实例验证,与改进的遗传算法进行对比,子集模拟算法在最优解的获取上具有更好的稳定性。
In order to efficiently and stably solve the time-cost-carbon emission target equilibrium problem in the production process of precast components,an optimization algorithm based on subset simulation is proposed.First,according to the importance of the three goals of time,cost and carbon emissions,by assigning weight coefficients,construct a multi-mode prefabricated component production goal equilibrium optimization model,and transform the model decision variables,and use real number coding to solve the problem Solve.Secondly,based on the model constraints,In order to obtain a reasonable initial population,an initial sample point generation method combining random generation and Markov Chain Monte Carlo Simulation(MCMCS)is proposed.In the iterative process of subset simulation,in order to increase the diversity of samples,MCMCS with evenly spaced points is adopted to improve the search ability of this method in the global scope.Finally,through example verification,compared with the improved genetic algorithm,the subset simulation algorithm has better stability in obtaining the optimal solution.
作者
王家
金艳琪
陈雅含
WANG Jia;JIN Yanqi;CHEN Yahan(College of Engineering,Hunan University,Changsha,Hunan 410082,China)
出处
《公路工程》
2022年第5期189-196,共8页
Highway Engineering
基金
中国博士后科学基金项目(2017M622575)。
