SIMULTANEOUS SCHEDULING OF MACHINES AND AGVs BY USING BLACK WIDOW SPIDER OPTIMIZATION ALGORITHM

This paper introduces a novel approach to address scheduling complexities in manufacturing environments by simultaneously optimizing machines and Automated Guided Vehicles (AGVs). Employing the Black Widow Spider Optimization Algorithm (BWSOA), inspired by the hunting behavior of black widow spiders, the study aims to minimize make-span, reduce idle time, and enhance overall system productivity. Through the BWSOA, jobs and operations are efficiently allocated to machines and AGVs. Benchmark problems are utilized to evaluate the effectiveness of the proposed methodology against existing scheduling methods. The findings demonstrate promising results, indicating that the BWSOA effectively minimizes make-span, mitigates idle time, and improves system productivity compared to conventional approaches. However, the study acknowledges limitations in the generalizability of findings and suggests further research to refine parameters and explore applicability across diverse manufacturing settings. This work offers practical implications for manufacturing practitioners, suggesting that implementation of the BWSOA can optimize resource allocation, decrease downtime, and enhance competitiveness and profitability in manufacturing operations.