A multiobjective hybrid imperialist competitive algorithm for multirobot cooperative assembly line balancing problems with energy awareness

Abstract

The environmental and economic pressures caused by energy consumption arouse energy-saving consciousness of the manufacturing industry. In recent years, robots have been extensively used in assembly systems as called robotic assembly lines where the energy consumption is a major expense, particularly in the workstation with the multirobot cooperative assembly of multirobot. To deal with this problem, the paper presents a novel mathematical model with three objectives of minimizing the cycle time, the sum of energy consumption, and the total cost of robots of assembly lines. Due to the nondeterministic polynomial time nature of the considered problem, a multiobjective hybrid imperialist competitive algorithm with nondominated sorting strategy is developed, which uses a representation technique of three-level coding, i.e. the station level, the task level, and the robot level and proposes an original concept of workstation decision assignment matrix to identify the performed tasks by the same type of robots in a workstation. Furthermore, a late-acceptance hill-climbing algorithm is combined into the algorithm to improve the performance of the proposed algorithm. Finally, testing cases are designed to measure the performance of the proposed method by comparing with two other high-performing multiobjective methods. The computational and statistical results show that the proposed multiobjective hybrid imperialist competitive algorithm is conducive to improve the line efficiency, to reduce the sum of energy consumption, and to cut the total cost of robots in an assembly line effectively.