Paper Info
Title
SPAM: Set Preference Algorithm for Multiobjective Optimization
Abstract
This paper pursues the idea of a general multiobjective optimizer that can be flexibly adapted to arbitrary user preferences--assuming that the goal is to approximate the Pareto-optimal set. It proposes the Set Preference Algorithm for Multiobjective Optimization (SPAM) the working principle of which is based on two observations: (i) current multiobjective evolutionary algorithms (MOEAs) can be regarded as hill climbers on set problems and (ii) specific user preferences are often (implicitly) expressed in terms of a binary relation on Pareto set approximations. SPAM realizes a (1 + 1)-strategy on the space of Pareto set approximations and can be used with any type of set preference relations, i.e., binary relations that define a total preorder on Pareto set approximations. The experimental results demonstrate for a range of set preference relations that SPAM provides full flexibility with respect to user preferences and is effective in optimizing according to the specified preferences. It thereby offers a new perspective on preference-guided multiobjective search.
Year
DOI
Venue
2008
10.1007/978-3-540-87700-4_84
PPSN
Keywords
Field
DocType
set preference relation,user preference,set problem,general multiobjective optimizer,specific user preference,set preference algorithm,preference-guided multiobjective search,pareto-optimal set,multiobjective optimization,binary relation,current multiobjective evolutionary algorithm,arbitrary user preference
Hill climbing,Evolutionary algorithm,Computer science,Binary relation,Multi-objective optimization,Artificial intelligence,Preference relation,Mathematical optimization,Algorithm,Evolutionary computation,Preorder,Machine learning,Pareto principle
Conference
Volume
ISSN
Citations 
5199
0302-9743
26
PageRank 
References 
Authors
1.26
16
3
Name
Order
Citations
PageRank
Eckart Zitzler14678291.01
Lothar Thiele214025957.82
Johannes Bader369418.64