Scheduling problems in the apparel industries: a systematic literature review

Abstract

Purpose Scheduling is vital for throughput and delivery in apparel manufacturing but is hindered by labor-intensive processes and high product variety. This study aims to systematically review scheduling models (2005–2025) for cutting and sewing operations. Design/methodology/approach Following preferred reporting items for systematic reviews and meta-analyses 2020, a systematic search across major databases identified 340 records, with 82 studies meeting inclusion criteria. Findings Research evolved from deterministic and heuristic models (2005–2010) toward stochastic models and bi-objective optimization (2011–2019). Since 2020, a shift toward Industry 4.0 (Internet of Things, digital twins) and human-centered approaches has emerged. Most studies originate from Asia and Europe, reflecting global manufacturing hubs. Research limitations/implications The review is restricted to 82 English-language studies from selected databases published within the 2005–2025 timeframe. Practical implications Manufacturers should adopt hybrid, real-time scheduling to mitigate bottlenecks and support efficiency. Social implications Manufacturers should adopt ergonomic and human-centered models to enhance worker well-being. Originality/value This review identifies a paradigm shift from single-objective optimization to adaptive, data-driven and human-centric models in the apparel industry.