Paper Info
Title
Evolving L-systems as an intelligent design approach to find classes of difficult-to-solve traveling salesman problem instances
Abstract
The technique of computationally analysing a program by searching for instances which causes the program to run in its worst-case time is examined. Concorde [2], the state-of-the-art Traveling Salesperson Problem (TSP) solver, is the program used to test our approach. We seed our evolutionary approach with a fractal instance of the TSP, defined by a Lindenmayer system at a fixed order. The evolutionary algorithm produced modifications to the L-System rules such that the instances of the modified L-System become increasingly much harder for Concorde to solve to optimality. In some cases, while still having the same size, the evolved instances required a computation time which was 30,000 times greater than what was needed to solve the original instance that seeded the search. The success of this case study shows the potential of Evolutionary Search to provide new test-case scenarios for algorithms and their software implementations.
Year
DOI
Venue
2011
10.1007/978-3-642-20525-5_1
EvoApplications (1)
Keywords
Field
DocType
worst-case time,lindenmayer system,fractal instance,modified l-system,computation time,l-system rule,evolving l-systems,intelligent design approach,evolutionary search,original instance,evolutionary algorithm,evolutionary approach,salesman problem instance,traveling salesman problem,fractals,intelligent design,l systems,traveling salesperson problem
Intelligent design,Mathematical optimization,Evolutionary algorithm,Computer science,Fractal,Travelling salesman problem,Solver,Software implementation,Computation
Conference
Volume
ISSN
Citations 
6624
0302-9743
3
PageRank 
References 
Authors
0.42
4
2
Name
Order
Citations
PageRank
Farhan Ahammed1152.43
Pablo Moscato233437.27