Exploration of applying statistical process control strategies to simulated annealing optimization techniques

Simulated annealing is a global stochastic optimization technique that is popular for engineers seeking efficient solutions to optimization problems. One area for algorithm enhancement is improving its efficiency. This paper explores the potential of detecting productive search at each temperature using statistical process control (SPC) concepts. The proposed Detection of Productive Search (DPS) annealing schedule has already been compared to three other viable schedules using a 100-city traveling salesman problem. DPS results are on par with more traditional schedules while using less iterations. The performance of three DPS techniques is presented here. They are: (1) X-Bar charting; (2) moving average charts; and (3) cumulative sum charting using decision interval format