Abstract
Paper aims: This paper proposes a warehouse design framework for evaluating the most robust combination of layout alternatives, tactical (picking, storage) and operational (routing) control policies, considering simultaneously the service level, costs and resource utilization criteria. Originality: We applied an innovative Morphological Analysis to reduce the number of alternatives and evaluate the uncertainties in warehouse design. We also address the effect of congestion and options for configuring the layout of aisles. Research method: We apply multicriteria decision analysis and discrete event simulation to evaluate the most robust combination between layout alternatives and operational control policies. We also suggest the use of scenario planning to deal with the high uncertainties involved in the order picking activity. Main findings: Our framework captures the warehouse manager’s preference and experience by means of weight elicitation, value functions, scenario planning and an inter-scenario robustness index to provide a robust final solution. Implications for theory and practice: For theory, we highlight the combination of methods applied to a strategic, tactical and operational warehouse design problem in an environment with uncertainties. For practice, warehouse managers may use the framework to explore and find out which combination of control policies and layout can meet the company’s objectives.
| Original language | English |
|---|---|
| Article number | e20240004 |
| Journal | Production |
| Volume | 34 |
| DOIs | |
| State | Published - 2024 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Keywords
- Discrete event simulation
- Multicriteria decision analysis
- Scenario planning
- Warehouse control policies
- Warehouse layout
ASJC Scopus subject areas
- Industrial and Manufacturing Engineering