An Improved Particle Swarm Optimization Algorithm for Scheduling of Single Mobile Robot

Abstract

With technological innovations in the area of mobile robotics, nowadays there are numerous mobile robotic platforms ready for integration in manufacturing systems. When mobile robots are integrated into these systems, their scheduling is one of the necessary tasks for increasing the productivity of the whole system. For small and medium size enterprises (SMEs), the integration of mobile robot into a scheduling system can be a challenging and difficult task. In this paper, the authors develop the model for integration and scheduling of single mobile robot for transportation tasks in intelligent manufacturing environment. The complex combinatorial optimization problem of manufacturing resource scheduling can be solved by using wellestablished metaheuristic algorithms. The authors propose an improved Particle Swarm Optimization (iPSO) algorithm for solving this problem. The traditional PSO algorithm is enhanced by using chaos theory. Chaotic maps enhance the ability to extensively search state-space and skip local minima. Ten chaotic maps are thoroughly tested on 23 benchmark problems and the Tent map shows the best performance. All the algorithms are implemented and tested in MATLAB software environment.