An Improved Immune Clone Selection Algorithm for Multi Robot Task Scheduling

Abstract

The main aim of this study is managing robot tasks to minimize the deviation between the resource requirements and stated desirable levels. An improved adaptive immune clone selection algorithm (ICSA) is proposed. In this study resource leveling methods are used to solve task scheduling problems in autonomous multi robot group. Robots are considered as resources. The experimental results show that proposed methods have better performances such as good and fast global convergence, strong robustness, insensitive to initial values, simplicity of implementation.