计算理论
数学优化
数学
多目标优化
帕累托原理
集合(抽象数据类型)
非线性系统
帕累托最优
计算机科学
算法
量子力学
物理
程序设计语言
作者
Regina S. Burachik,C. Yalçın Kaya,M. M. Rizvi
标识
DOI:10.1007/s10957-013-0346-0
摘要
We introduce and analyze a novel scalarization technique and an associated algorithm for generating an approximation of the Pareto front (i.e., the efficient set) of nonlinear multiobjective optimization problems. Our approach is applicable to nonconvex problems, in particular to those with disconnected Pareto fronts and disconnected domains (i.e., disconnected feasible sets). We establish the theoretical properties of our new scalarization technique and present an algorithm for its implementation. By means of test problems, we illustrate the strengths and advantages of our approach over existing scalarization techniques such as those derived from the Pascoletti–Serafini method, as well as the popular weighted-sum method.
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