摘要
在铁合金配料问题的大量传统研究工作中,多数研究工作均与确定性系统相关。在不确定系统中考虑一类新的带有可信性约束的模糊铁合金配料机会约束模型。由于提出的模糊铁合金配料问题常常包含带有无限支撑的模糊变量参数,因此它是一个很少被直接求解的无穷维优化问题。为了求解这个模糊优化问题,通过逼近方法将模糊铁合金配料机会约束问题转化为一个有限维优化问题。设计一个含有逼近方法、神经网络和遗传算法的混合智能算法求解提出的带有可信性约束的铁合金配料机会约束问题。给出一个数值例子来表明所设计模型和算法的实用性。
A great deal of conventional research has been done on ferroalloy burdening problem,most of which concerns deterministic systems.This paper considers a new class of fuzzy ferroalloy burdening chance-constrained model with credibility constraint in uncertainty systems.Since the proposed fuzzy ferroalloy burdening problem often includes fuzzy variable parameters with infinite supports,it is infinite-dimensional optimization problem that can rarely be solved directly.In order to solve this fuzzy programming problem,it transforms fuzzy ferroalloy burdening chance-constrained problem into a finite-dimensional optimization problem by approximation approach.It designs a hybrid intelligent algorithm,which combines approximation approach,neural network and genetic algorithm to solve the proposed ferroalloy burdening chance-constrained problem with credibility constraint.A numerical example is given to show the practicality of the designed model and algorithm.
出处
《计算机工程与应用》
CSCD
北大核心
2011年第36期238-241,共4页
Computer Engineering and Applications
基金
河北省高等学校自然科学研究青年基金项目(No.2010124)
河北省科学技术研究与发展计划科研基金项目(No.104572113)
关键词
铁合金配料问题
可信性约束
机会约束
逼近方法
神经网络
遗传算法
ferroalloy burdening problem
credibility constraint
chance-constrained
approximation approach
neural network
genetic algorithm
