Bi-objective robust optimisation

被引:39
|
作者
Kuhn, K. [1 ]
Raith, A. [2 ]
Schmidt, M. [3 ]
Schoebel, A. [4 ]
机构
[1] RAND Corp, Santa Monica, CA 90406 USA
[2] Univ Auckland, Dept Engn Sci, Auckland, New Zealand
[3] Erasmus Univ, Dept Technol & Operat Management, Rotterdam, Netherlands
[4] Univ Gottingen, Inst Numer & Appl Math, D-37073 Gottingen, Germany
关键词
Multiple objective programming; Robust optimisation; OR in transportation; MULTIOBJECTIVE OPTIMIZATION; EFFICIENT SET;
D O I
10.1016/j.ejor.2016.01.015
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
It is important, in practice, to find robust solutions to optimisation problems. This issue has been the subject of extensive research focusing on single-objective problems. Recently, researchers also acknowledged the need to find robust solutions to multi-objective problems and presented some first results on this topic. In this paper, we deal with bi-objective optimisation problems in which only one objective function is uncertain. The contribution of our paper is three-fold. Firstly, we introduce and analyse four different robustness concepts for bi-objective optimisation problems with one uncertain objective function, and we propose an approach for defining a meaningful robust Pareto front for these types of problems. Secondly, we develop an algorithm for computing robust solutions with respect to these four concepts for the case of discrete optimisation problems. This algorithm works for finite and for polyhedral uncertainty sets using a transformation to a multi-objective (deterministic) optimisation problem and the recently published concept of Pareto robust optimal solutions (lancu & Trichakis, 2014). Finally, we apply our algorithm to two real-world examples, namely aircraft route guidance and the shipping of hazardous materials, illustrating the four robustness concepts and their solutions in practical applications. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:418 / 431
页数:14
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