Examining the criteria for the location of passing load gauges with ANP and Fuzzy DEMATEL methods (Case study: Arta Profile Ardabil Company)

Fazayeli, Saeed; Harir, Mohammad; Komari Alaei, Mohammad Reza

doi:10.22034/jtd.2025.2029511.1935

Examining the criteria for the location of passing load gauges with ANP and Fuzzy DEMATEL methods (Case study: Arta Profile Ardabil Company)

Document Type : Research Paper

Authors

Saeed Fazayeli ¹

Mohammad Harir ²

Mohammad Reza Komari Alaei ³

¹ Industrial Engineering Department, Technical and Engineering faculty, Urmia University, Urmia, Iran

² Industrial Engineering Department, Al Ghadir Institute of Higher Education, Tabriz, Iran

³ Department of Business Administration, Hacettepe University, Ankara, TURKEY

10.22034/jtd.2025.2029511.1935

Abstract

In most manufacturing environments, it is difficult to ship directly from the manufacturer to the customer. Therefore, a middle point is necessary for the communication between manufacturers and customers. The traditional warehouse is not favored by current companies due to the cost of maintaining the inventory and laborious labor costs of order selection, storage and order taking. Therefore, logistics techniques that can help reduce inventory costs while increasing the flow of goods and shortening the transportation cycle are a significant approach for these companies. A transit loader is a special type of warehouse where the received products are immediately loaded to the exit dock door within 24 hours. As a result, order picking and storage activities can be minimized or eliminated.
The purpose of this research is to investigate the location criteria of transit load (case study: Ardabil Arta Profile Company). The statistical population of this research includes all industrial engineers, production planners based in Arta Profile Company, Ardabil. According to Thomas Saati, 10 industry experts have been selected as a statistical sample. The tool used in this research is a researcher-made questionnaire. In this research, the ANP method is used to prioritize the location of the transit load and to prioritize it, and the Fuzzy DEMATEL method is used to identify the severity of the cause and effect relationships of the transit load location. For this purpose, 28 criteria have been selected according to the opinion of industry experts. The results obtained from the network analysis method show that the first criterion of the vehicle routing problem with a value of 0.34 is higher than the rest of the dimensions. The results of the Fuzzy Dimetal method show that the distribution centers are in the first place, the reduction of delivery/distribution operations is in the second place, and the cost of lateness and early delivery is in the last place.

Keywords

ANP method

fuzzy dimethyl

transit loading

location

Subjects

Research and Development

Babazadeh, R., Jolai, F., Razmi, J., & Pishvaee, M. S. (2014). Developing a robust programming approach for the responsive logistics network design under uncertainity. International Journal of Industrial Engineering, 21(1).

Buakum, D., & Wisittipanich, W. (2019, March). A literature review and further research direction in cross-docking. In Proceedings of the International Conference on Industrial Engineering and Operations Management (pp. 471-481).

Darvishi, F., Yaghin, R. G., & Sadeghi, A. (2020). Integrated fabric procurement and multi-site apparel production planning with cross-docking: A hybrid fuzzy-robust stochastic programming approach. Applied Soft Computing, 92, 106267.

Dondo, R., & Cerdá, J. (2014). A monolithic approach to vehicle routing and operations scheduling of a cross-dock system with multiple dock doors. Computers & Chemical Engineering, 63, 184-205.

Hasani Goodarzi, A., Zegordi, S. H., Alpan, G., Nakhai Kamalabadi, I., & Husseinzadeh Kashan, A. (2021). Reliable cross-docking location problem under the risk of disruptions. Operational Research, 21(3), 1569-1612.

Gümüş, M., & Bookbinder, J. H. (2004). Cross‐docking and its implications in location‐distribution systems. Journal of Business logistics, 25(2), 199-228.

Ladier, A. L., & Alpan, G. (2016). Cross-docking operations: Current research versus industry practice. Omega, 62, 145-162.

Javanmard, S., Vahdani, B., & Tavakkoli-Moghaddam, R. (2014). Solving a multi-product distribution planning problem in cross docking networks: An imperialist competitive algorithm. The International Journal of Advanced Manufacturing Technology, 70(9), 1709-1720.

Moghadam, S. S., Ghomi, S. F., & Karimi, B. (2014). Vehicle routing scheduling problem with cross docking and split deliveries. Computers & chemical engineering, 69, 98-107.

Mousavi, S. M., & Tavakkoli-Moghaddam, R. (2013). A hybrid simulated annealing algorithm for location and routing scheduling problems with cross-docking in the supply chain. Journal of manufacturing systems, 32(2), 335-347.

Mousavi, S. M., Antuchevičienė, J., Zavadskas, E. K., Vahdani, B., & Hashemi, H. (2019). A new decision model for cross-docking center location in logistics networks under interval-valued intuitionistic fuzzy uncertainty. Transport, 34(1), 30-40.

Musa, R., Arnaout, J. P., & Jung, H. (2010). Ant colony optimization algorithm to solve for the transportation problem of cross-docking network. Computers & Industrial Engineering, 59(1), 85-92.

Rahbari, A., Nasiri, M. M., Werner, F., Musavi, M., & Jolai, F. (2019). The vehicle routing and scheduling problem with cross-docking for perishable products under uncertainty: Two robust bi-objective models. Applied Mathematical Modelling, 70, 605-625.

Shahabi-Shahmiri, R., Asian, S., Tavakkoli-Moghaddam, R., Mousavi, S. M., & Rajabzadeh, M. (2021). A routing and scheduling problem for cross-docking networks with perishable products, heterogeneous vehicles and split delivery. Computers & industrial engineering, 157, 107299.

Sung, C. S., & Song, S. H. (2003). Integrated service network design for a cross-docking supply chain network. Journal of the Operational Research Society, 54(12), 1283-1295.

Sung, C. S., & Yang, W. (2008). An exact algorithm for a cross-docking supply chain network design problem. Journal of the Operational Research Society, 59(1), 119-136.

Teece, D. J. (2010). Business models, business strategy and innovation. Long range planning, 43(2-3), 172-194.

Van Belle, J., Valckenaers, P., & Cattrysse, D. (2012). Cross-docking: State of the art. Omega, 40(6), 827-846.

Reference (In Persian)

Emadabadi, A.A., Teimoury, E., Pishvaee, M.S. (2019). Design of Multi-Periodical and Multi-Product Supply Chain Network with Regard to Disruption of Facilities and Communication Paths (Case Study: Subscription Plan for Publications), , Industrial Management Perspective, 9(3), 135-163.

Ghaffari Touran, H., Badali, H. (2017).Cross-Docking Operations: Current Research versus Industry Practice, Supply Chain Management, 19(57), 93-121.

Ghiasi, H.R., Musavi, S.M., Azimi, F. (2021). Truck scheduling in a cross-dock warehouse considering reverse logistics and cargo sorting in a gray environment, Fourth International Conference on Soft Computing.

Ghorbani, S., Afshar-Nadjafi, B. (2021). Modeling and Solving the Cross-Docking Centers Location and Vehicle Scheduling Problem in a Multi-Product Supply Chain with Discrete Pick-up and Delivery, Industrial Management Perspective, 11(2), 41-66.

Rezaei, S., Kheirkhah, A.S. (2015). Applying Cross-Docking Operations in Logistics Network Design: Analysis and Literature Review, Supply Chain Management, 17(49), 118-135.