A Sensitive Metaheuristic for Solving a Large Optimization Problem

Abstract

A metaheuristic for solving complex problems is proposed. The introduced Sensitive Robot Metaheuristic (SRM) is based on the Ant Colony System optimization technique. The new model relies on the reaction of virtual sensitive robots to different stigmergic variables. Each robot is endowed with a particular stigmergic sensitivity level ensuring a good balance between search diversification and intensification. Comparative tests are performed on large-scale NP-hard robotic travel problems. These tests illustrate the effectiveness and robustness of the proposed metaheuristic.