An efficient PSO for type II robotic assembly line balancing problem

In this modern world of technology, robots are extensively used in an assembly line. Different robots may be allocated to the assembly tasks, and each robot requires different assembly times to perform a given task, because of its capabilities and specialization in robotic assembly line systems. Use of robots helps us to improve the productivity of the line and increases the quality of the product. To find an optimal solution for Robotic Assembly Line Balancing (rALB) problem we will have to assign robots to stations in a balanced manner to perform activities. The main objective of this work is to minimize the cycle time and maximize the production rate of the line. A particle swarm optimization method is proposed to find optimum solution for the rALB problem. Results obtained using the PSO are further improved by using a local exchange procedure. Performance of the proposed method is tested on benchmark rALB problems. The results of PSO are found to be better than the methods reported in the literature and it produce consistent results.