The Coordination of Parallel Search with Common Components Stephen Chen and Gregory Pitt York University

Heuristic Search Search Operators Control Strategies June 23, 2005 IEA-AIE 2005

An Obvious Failing Point search operators do not have historical information! June 23, 2005 IEA-AIE 2005

Search Operator Strategies What can be improved? What is worth keeping? June 23, 2005 IEA-AIE 2005

Random Local Minima June 23, 2005 IEA-AIE 2005

Simulated Annealing June 23, 2005 IEA-AIE 2005

Summary Random search space, random search strategy All the intelligence of simulated annealing is in the control strategy June 23, 2005 IEA-AIE 2005

Distribution of Local Minima (Boese) Length Average distance from other local minima June 23, 2005 IEA-AIE 2005

“Big-Valley” – Globally Convex June 23, 2005 IEA-AIE 2005

“Directed” Simulated Annealing June 23, 2005 IEA-AIE 2005

Coordination with Common Components June 23, 2005 IEA-AIE 2005

Restricted Mutations Parent 1 1 1 1 0 0 1 0 1 1 1 Common 1 1 0 1 1 1 Uncommon 1 1 0 0 1 Uncommon 2 0 1 1 0 June 23, 2005 IEA-AIE 2005

TSP Results Instance n=1 n=2 n=4 n=8 pcb1173 8.55 8.07 5.08 8.05 4.88 7.49 4.40 fl1400 5.82 4.33 3.15 3.58 2.45 2.86 1.94 fl1577 10.97 9.09 2.48 7.69 2.19 6.91 1.49 June 23, 2005 IEA-AIE 2005

Summary Globally convex search space, “respectful” search operator Add some intelligence to the search operator June 23, 2005 IEA-AIE 2005

Conclusion The preservation of common components can improve the performance of parallel search procedures in globally convex search spaces June 23, 2005 IEA-AIE 2005