Volume 55, 2021Regular articles published in advance of the transition of the journal to Subscribe to Open (S2O). Free supplement sponsored by the Fonds National pour la Science Ouverte
|Page(s)||S1369 - S1394|
|Published online||02 March 2021|
Leagile supply chain network design through a dynamic two-phase optimization in view of order penetration point
School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
2 Department of Industrial Engineering, Khatam University, Tehran, Iran
* Corresponding author: email@example.com
Accepted: 22 April 2020
In the contemporary world, combining the concept of agile and lean manufacturing (LM) is one of the most strategic and appealing concerns in the industrial environments. In this paper, a new Leagile structure is proposed for a supply chain. This research covers long term and mid-term horizon by designing a supply chain network up to the order penetration point (OPP) and final assembly and sale planning respectively. The problem is programmed in two phases. First, a bi-objective optimization is developed to minimize the total cost related with LM. In the second phase, the total cost and the customer service level (CSL) are considered as the agile manufacturing (AM) architecture. In the proposed model, a utility function is applied to set balance between the price and customer satisfaction. In addition, a robust credibility-based fuzzy programming (RCFP) is developed to handle uncertainty of the first phase. The proposed model and the solution method are implemented for a real industrial case study to show the applicability and usefulness of this study. According to the results, improving the customer service level can enhance the total cost of the second phase meaning that customer responsiveness price is too high for the proposed system.
Mathematics Subject Classification: 90B06
Key words: Leagile manufacturing / supply chain network design / order penetration point / robust optimization / credibility measure
© EDP Sciences, ROADEF, SMAI 2021
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