Improved Fireworks Algorithm for Multi-Objective Hybrid Disassembly Line Balancing Problem With Consideration of Machine Wear Rate

This work aims to address the hybrid disassembly line balancing problem with multiple types of robots and multiple objectives. It investigates how intelligent algorithms can optimize task allocation and disassembly line planning to enhance overall efficiency and balance. Leveraging the advantages of swarm intelligence algorithms in global searching and environmental adaptability, an improved fireworks algorithm is proposed. A multi-objective hybrid disassembly line balancing problem that integrates linear and U-shaped disassembly lines is presented. Its target is to maximize profit and minimize total robot energy consumption while considering machine wear rates. We compare the improved fireworks algorithm with NSGA-II and MOEA/D algorithms through simulation experiments. Results indicate that the improved fireworks algorithm is more effective and outperforms other methods in solving the hybrid disassembly line balancing problem.