摘要
充分考虑投入产出平衡约束中的随机变量和模糊变量,结合投入产出最优控制模型建立多目标产业结构优化最优控制模型。考虑能源消耗和污染物排放均为随机变量,并针对不同随机变量所代表的实际意义假设其满足不同的分布函数,运用随机规划和模糊规划方法将模型转化为确定性规划问题,采用评价函数和惩罚函数法将模型转化为无约束最优化问题。根据黄岛区数据利用粒子群算法对模型进行求解,给出最优控制和最优轨线。研究结果可以用来确定行业发展速度和规模,为制定产业结构优化政策提供决策帮助。
Considering stochastic variables and fuzzy variables in input-output equilibrium constraints,a multi-objective optimal control model of industrial structure optimization was developed by combining with an input-output optimal control model.Energy consumption and pollutant discharge are considered as stochastic variables.Different distribution functions are assumed according to the stochastic variables actual significance.Stochastic and fuzzy programming methods are used to convert the model into a definite one.Evaluation and penalty function methods are adopted to transform the model into an unconstrained optimization problem.On the basis of actual data in Huangdao,the model was solved by using particle swarm optimization algorithm.The optimal control and optimal trajectory were given.The results can determine the developmental speed and scale of all industries,which can provide decision-making aid for formulating industrial structure optimization policies.
出处
《中国石油大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2011年第2期182-187,共6页
Journal of China University of Petroleum(Edition of Natural Science)
基金
国家自然科学基金项目(60974039)
关键词
投入产出
供需平衡
产业结构优化
粒子群算法
input-output
balance between supply and demand
industrial structure optimization
particle swarm optimization algorithm
