摘要
不确定规划广泛用于处理不确定环境下的优化问题,比如车辆调度问题、网络优化问题、作业排序问题等。本文在不确定理论框架下,建立一个应急海运路径运输的不确定规划模型,同时考虑路径行进时间、风险和约束变量的置信水平,利用Pareto最优解的遗传算法进行求解,最后通过两个数值实例验证了该模型的有效性和实用性。
Uncertain programming is widely used to deal with optimization problems in uncertain environments,such as vehicle scheduling,network optimization,job sequencing,etc.In this paper,we establish an uncertain planning model for emergency maritime route transportation under the framework of uncertainty theory.Considering the path travel time,path risk and the confidence level of constraint variable,the genetic algorithm of Pareto optimal solution is introduced to solve the model.Finally,two numerical examples are given to verify the effectiveness and practicability of the model.
作者
王志刚
曹楚昕
吕钰儿
申康
WANG Zhi-gang;CAO Chu-xin;LV Yu-er;SHEN Kang(School of Science,Hainan University,Haikou 570228,China)
出处
《模糊系统与数学》
北大核心
2023年第6期158-164,共7页
Fuzzy Systems and Mathematics
基金
海南省自然科学基金高层次人才项目(2019RC168)
海南省科协青年科技英才创新计划(QCXM201806)
关键词
不确定理论
应急海运路径
不确定规划
Pareto遗传算法
Uncertainty Theory
Emergency Maritime Route
Uncertain Programming Model
Pareto Optimal Solution
Genetic Algorithm
