Best Path in Mountain Environment based on Parallel Hill Climbing Algorithm

Abstract

Heuristic search is a search process that uses domain knowledge in heuristic rules or procedures to direct the progress of a search algorithm. Hill climbing is a heuristic search technique for solving certain mathematical optimization problems in the field of artificial intelligence. In this technique, starting with a suboptimal solution is compared to starting from the base of the hill, and improving the solution is compared to walking up the hill. The optimal solution of the hill climbing technique can be achieved in polynomial time and is an NP-complete problem in which the numbers of local maxima can lead to an exponential increase in computational time. To address these problems, the proposed hill climbing algorithm based on the local optimal solution is applied to the message passing interface, which is a library of routines that can be used to create parallel programs by using commonly available operating system services to create parallel processes and exchange information among these processes. Experimental results show that parallel hill climbing outperforms sequential methods.