Evolutionary algorithms have been shown to be very successful in solving multi-objective optimization problems(MOPs).However,their performance often deteriorates when solving MOPs with irregular Pareto fronts.To remed...Evolutionary algorithms have been shown to be very successful in solving multi-objective optimization problems(MOPs).However,their performance often deteriorates when solving MOPs with irregular Pareto fronts.To remedy this issue,a large body of research has been performed in recent years and many new algorithms have been proposed.This paper provides a comprehensive survey of the research on MOPs with irregular Pareto fronts.We start with a brief introduction to the basic concepts,followed by a summary of the benchmark test problems with irregular problems,an analysis of the causes of the irregularity,and real-world optimization problems with irregular Pareto fronts.Then,a taxonomy of the existing methodologies for handling irregular problems is given and representative algorithms are reviewed with a discussion of their strengths and weaknesses.Finally,open challenges are pointed out and a few promising future directions are suggested.展开更多
调整优化城市土地利用结构与布局,实现社会经济发展和生态保护的协同优化是城市土地利用规划管理和决策的关键。该研究使用多目标规划(multiple objective planning,MOP)模型和未来土地利用模拟(future land use simulation model,FLUS...调整优化城市土地利用结构与布局,实现社会经济发展和生态保护的协同优化是城市土地利用规划管理和决策的关键。该研究使用多目标规划(multiple objective planning,MOP)模型和未来土地利用模拟(future land use simulation model,FLUS)模型相结合的方法,运用权衡分析制定多目标权衡下的土地利用优化配置情景方案,以期为杭州市土地利用优化配置规划和管理提供科学参考。结果表明:1)通过耦合MOP模型和FLUS模型,从土地利用生态-经济转化效率视角可以有效实现土地利用结构和布局的优化配置情景模拟。2)通过比较单位经济效益的减少比例可产生的生态效益增加比例,确定土地利用经济与生态效益权重比例为4:6的发展情景是权衡土地利用社会、经济和生态效益下的杭州市土地利用结构最优方案。3)最优土地利用结构方案的建设用地扩张规模介于经济发展优化和生态保护优先情景方案间,耕地规模较其他情景方案减少幅度放缓,在空间上减少对生态用地的侵占,土地利用景观格局破碎度和复杂性降低。该研究的方法和结果可为区域土地利用规划决策和可持续发展提供理论与应用参考。展开更多
基金supported in part by the National Natural Science Foundation of China(61806051,61903078)Natural Science Foundation of Shanghai(20ZR1400400)+2 种基金Agricultural Project of the Shanghai Committee of Science and Technology(16391902800)the Fundamental Research Funds for the Central Universities(2232020D-48)the Project of the Humanities and Social Sciences on Young Fund of the Ministry of Education in China(Research on swarm intelligence collaborative robust optimization scheduling for high-dimensional dynamic decisionmaking system(20YJCZH052))。
文摘Evolutionary algorithms have been shown to be very successful in solving multi-objective optimization problems(MOPs).However,their performance often deteriorates when solving MOPs with irregular Pareto fronts.To remedy this issue,a large body of research has been performed in recent years and many new algorithms have been proposed.This paper provides a comprehensive survey of the research on MOPs with irregular Pareto fronts.We start with a brief introduction to the basic concepts,followed by a summary of the benchmark test problems with irregular problems,an analysis of the causes of the irregularity,and real-world optimization problems with irregular Pareto fronts.Then,a taxonomy of the existing methodologies for handling irregular problems is given and representative algorithms are reviewed with a discussion of their strengths and weaknesses.Finally,open challenges are pointed out and a few promising future directions are suggested.
文摘调整优化城市土地利用结构与布局,实现社会经济发展和生态保护的协同优化是城市土地利用规划管理和决策的关键。该研究使用多目标规划(multiple objective planning,MOP)模型和未来土地利用模拟(future land use simulation model,FLUS)模型相结合的方法,运用权衡分析制定多目标权衡下的土地利用优化配置情景方案,以期为杭州市土地利用优化配置规划和管理提供科学参考。结果表明:1)通过耦合MOP模型和FLUS模型,从土地利用生态-经济转化效率视角可以有效实现土地利用结构和布局的优化配置情景模拟。2)通过比较单位经济效益的减少比例可产生的生态效益增加比例,确定土地利用经济与生态效益权重比例为4:6的发展情景是权衡土地利用社会、经济和生态效益下的杭州市土地利用结构最优方案。3)最优土地利用结构方案的建设用地扩张规模介于经济发展优化和生态保护优先情景方案间,耕地规模较其他情景方案减少幅度放缓,在空间上减少对生态用地的侵占,土地利用景观格局破碎度和复杂性降低。该研究的方法和结果可为区域土地利用规划决策和可持续发展提供理论与应用参考。
