Nasser Tairan¹, Muhammad Asif Jan² and Rashida Adeeb Khanum³, ¹King Khalid University, KSA, ²Kohat University of Science & Technology, Pakistan and ³University of Peshawar, Pakistan

This paper proposes a Parallel Guided Local Search (PGLS) framework for continuous optimization. In PGLS, several guided local search (GLS) procedures (agents) are run for solving the optimization problem. The agents exchange information for speeding up the search. For example, the information exchanged could be knowledge about the landscape obtained by the agents. The proposed algorithm is applied to continuous optimization problems. The preliminary experimental results show that the algorithm is very promising.

Guided Local Search, Continuous Optimization Problems, Parallel Algorithms, Cooperative algorithms