Quantitative Comparison of Approximate Solution Sets for Bi-criteria Optimization Problems
Quantitative Comparison of Approximate Solution Sets for Bi-criteria Optimization Problems
复制标题
双准则优化问题近似解集的定量比较
DOI：
10.1111/1540-5915.02254
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发表时间：
2003
期刊：
影响因子：
--
通讯作者：
Bosun Kim
中科院分区：
文献类型：
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作者：
W. Carlyle;John W. Fowler;E. Gel;Bosun Kim
我们提出了综合偏好功能（IPF）的质量比较建议的近帕累托最优的解决方案，双标准优化问题。评价这些解集的质量是发展和比较多目标组合优化问题的算法的关键问题之一。IPF是一个集函数，给定决策者提供的权重密度函数和特定问题的离散解集，将数值分配给该解集。该值可以用于比较不同的解决方案集的质量，因此提供了一个强大的，定量的方法来比较不同的启发式，后验解决方案的过程中困难的多目标优化问题。我们提供了决策者偏好函数的具体例子，并说明了特定的解决方案集和一个简单的家庭的组合目标的计算所产生的IPF。
We present the Integrated Preference Functional (IPF) for comparing the quality of proposed sets of near-pareto-optimal solutions to bi-criteria optimization problems. Evaluating the quality of such solution sets is one of the key issues in developing and comparing heuristics for multiple objective combinatorial optimization problems. The IPF is a set functional that, given a weight density function provided by a decision maker and a discrete set of solutions for a particular problem, assigns a numerical value to that solution set. This value can be used to compare the quality of different sets of solutions, and therefore provides a robust, quantitative approach for comparing different heuristic, a posteriori solution procedures for difficult multiple objective optimization problems. We provide specific examples of decision maker preference functions and illustrate the calculation of the resulting IPF for specific solution sets and a simple family of combined objectives.