Title
Constraint Handling Guided by Landscape Analysis in Combinatorial and Continuous Search Spaces.
Abstract
The notion and characterisation of fitness landscapes has helped understand the performance of heuristic algorithms on complex optimisation problems. Many practical problems, however, are constrained, and when significant areas of the search space are infeasible, researchers have intuitively resorted to a variety of constraint-handling techniques intended to help the algorithm manoeuvre through infeasible areas and towards feasible regions of better fitness. It is clear that providing constraint-related feedback to the algorithm to influence its choice of solutions overlays the violation landscape with the fitness landscape in unpredictable ways whose effects on the algorithm cannot be directly measured. In this work we apply metrics of violation landscapes to continuous and combinatorial problems to characterise them. We relate this information to the relative performance of six well-known constraint-handling techniques to demonstrate how some properties of constrained landscapes favour particular constraint-handling approaches. For the problems with sampled feasible solutions, a bi-objective approach was the best performing approach overall, but other techniques performed better on problems with the most disjoint feasible areas. For the problems with no measurable feasibility, a feasibility ranking approach was the best performing approach overall, but other techniques performed better when the correlation between fitness values and the level of constraint violation was high.
Year
DOI
Venue
2019
10.1162/evco_a_00222
Evolutionary computation
Keywords
Field
DocType
Broken Hill Problem.,Combinatorial optimisation,Constraint handling,Continuous optimisation,Search space analysis
Heuristic,Fitness landscape,Artificial intelligence,Landscape analysis,Mathematics,Machine learning
Journal
Volume
Issue
ISSN
27
2
1530-9304
Citations 
PageRank 
References 
2
0.36
7
Authors
2
Name
Order
Citations
PageRank
Katherine Malan116212.77
Irene Moser220921.94