A Comparison of Traditional and Simple Evolutionary Hill-Climbing Methods for Solving Static and Recurrent Dynamic Constraint Satisfaction Problems

In this paper we compare the performance of Minton’s et al. min-conflicts hill-climbing (MCHC) algorithm [16], Wallace and Freuder’s MCHC algorithm [25], Morris’ breakout algorithm (BA) [17, 18], and modified variants of the BA that we developed on static constraint satisfaction problems (CSPs) and recurrent dynamic constraint satisfaction problems (rDCSPs). Also, we used a simple evolutionary hill-climber (SEHC) to solve rDCSPs. In this study, our results show that our modified variants of the BA and Morris’ BA are the most efficient algorithms in terms of average number of candidate solutions, average number of constraint checks, and average clock cycles on our CSPs. The largest population SEHC algorithm was the most efficient in terms of average solution instability on our rDCSPs.