Neutrosophic LOPCOW-ARAS model for prioritizing industry 4.0-based material handling technologies in smart and sustainable warehouse management systems

• Published in: Applied soft computing 2023-08, Vol.143, p.110400, Article 110400
• Main Authors: Simic, Vladimir, Dabic-Miletic, Svetlana, Tirkolaee, Erfan Babaee, Stević, Željko, Ala, Ali, Amirteimoori, Arash
• Format: Article
• Language: English
• Subjects: ARAS; Industry 4.0; Multi-criteria group decision-making; Type-2 neutrosophic number; Warehouse management system
• ISSN: 1568-4946; 1872-9681
• DOI: 10.1016/j.asoc.2023.110400

Industry 4.0 technologies embedded in the warehouse management system (WMS) are needed to improve the automation of material handling activities such as receiving, storing, picking, sorting, packaging, and delivering. This research aims to introduce a neutrosophic multi-criteria group decision-making tool that is intelligible in supporting the transition and upgrading of WMS with Industry 4.0-based solutions. This advanced two-stage model is based on the integration of the logarithmic percentage change-driven objective weighting (LOPCOW) method and the additive ratio assessment (ARAS) method under the type-2 neutrosophic number (T2NN) environment. In the first stage, T2NN-LOPCOW generates an objective importance vector of decision-making criteria. In the second stage, T2NN-ARAS based on the generalized weighted Heronian mean operator provides an advantageous order of Industry 4.0-based material handling technologies. T2NN-LOPCOW-ARAS brings the following novelties: ((i) to straightforwardly represent and explore interconnection levels between weights of criteria, ((ii) to provide wide-scoping insight into the stability of initial priority order, as well as a broad spectrum of flexible solutions, ((iii) to control the normalization procedure and minimize distortions due to the double-normalization backbone. The real-life case study of a logistics company from the Serbian grocery retail sector illustrates the practical applicability of T2NN-LOPCOW-ARAS. A practical evaluation framework is defined to comprehensively assess automated guided vehicles (AGVs), collaborative robotics, and drones. The sensitivity analyses show the high robustness of the proposed framework. The comparative investigation shows that T2NN-LOPCOW-ARAS is superior to the extant methods. The research findings show that AGVs are the most favorable Industry 4.0-based material handling solution. •Material handling technology selection in smart and sustainable WMS is addressed.•Advanced two-stage LOPCOW and ARAS-based type-2 neutrosophic model is introduced.•Proposed intelligible MCGDM tool can support the transition to smart warehousing.•The comparative investigation demonstrates the superiority of T2NN-LOPCOW-ARAS.•Managerial insights for selecting an Industry 4.0-based material handling technology.