Disassembly Line Balancing Design for Mixed-Model Disassembly Process Using a Modified Metaheuristic Approach
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Abstract
This study has two main objectives: to propose a mathematical model for the mixedmodel disassembly line balancing problem and to develop a customized solving technique. The model aims to minimize the disassembly line length and the number of opened stations while maximizing workload smoothness in a two-sided disassembly line. The solver, based on the particle swarm optimization (PSO) algorithm, was enhanced through a new discretization method and the survival sub-swarm PSO strategy, enabling it to handle multi objective optimization via Pareto optimality for constructing the elite list. To validate the approach, experiments were conducted on a top-loaded washing machine with different takt times (71, 80, 90, and 100 seconds). Four competitive algorithms—NSGA-II, SPEA2, BARON, and MINLP—were used for comparison. Performance was evaluated using three indicators: inverted generational distance (𝐼𝐺𝐷), hypervolume (𝐻𝑉), and ratio (𝑅). The results showed that the proposed method consistently outperformed the other algorithms, achieving superior accuracy, efficiency, and stability in delivering optimal and reliable solutions.
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