Abstract
The Simple Assembly Line Balancing Problem Type 1 (SALBP-1) is a widely embraced method in the industry for its simplicity in organizing production processes and enhancing efficiency. Consequently, a Differential Evolution Algorithm (DDE) using a backward task sequence was developed in this study to assist in production process management by determining the optimal number of stations. The efficacy of this method was assessed by juxtaposing it with heuristic approaches, including Longest Operation Time (LOT), Most Following Tasks (MFT), Ranked Positional Weight (RPW), Shortest Operation Time (SOT), Fewest Following Tasks (FFT), Ant Colony Optimization (ACO), Differential Evolution (DE), and Immune Genetic Algorithm (IGA). The findings reveal that DDE outperforms LOT, MFT, RPW, SOT, and FFT in discovering superior solutions and consistently matches solutions achieved by ACO, DE, and IGA methods across all problems. Notably, the DDE method exhibits a shorter time frame for solution discovery.
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