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Protocol: Systematic Literature Review on Multiproduct Lotsizing and Scheduling in Single-Machine Environments: A Theoretical-Empirical Analysis

Sep 2026 · WPOM : Working Papers on Operations Management · 1 citation · 36 references

Abstract

Multiproduct lot-sizing and scheduling in single-machine or single-resource environments constitutes a classical and still relevant problem in the field of operations management. It requires coordinating lot-size decisions, production scheduling or sequencing, and the use of a constrained production resource, under setup-related conditions such as setup times, setup costs, and sequence-dependent changeovers. This problem is commonly addressed through the Economic Lot Scheduling Problem (ELSP). Although various models have been developed in the literature, their application in real industrial contexts has been less explored. In this context, the present protocol proposes the design of a systematic literature review aimed at analyzing multiproduct lot-sizing and scheduling in single-machine environments from a theoretical-empirical perspective. In particular, the review will examine the modelling assumptions and methodological approaches used in these studies, the level of empirical or industrial evidence supporting them, the factors influencing their adoption in industrial contexts, and the incorporation of sustainability and resilience criteria. The protocol also defines a structured search strategy based on conceptual search blocks, together with inclusion and exclusion criteria that distinguish between parametric and content-based criteria. This structure is intended to improve transparency, coherence, and traceability in the study selection process. The expected contribution is a systematic and reproducible review design capable of comparing formal model development with industrial applications. The review is expected to identify patterns in model formulation, levels of empirical evidence, adoption-related factors, and emerging research directions associated with sustainability, resilience, and advanced solution approaches.

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