Title: Analysing a fuzzy integrated inventory-production-distribution planning problem with maximum NPV of cash flows in a closed-loop supply chain
Authors: Amir Hossein Nobil; Ata Allah Taleizadeh
Addresses: Faculty of Mechanical and Industrial Engineering, Islamic Azad University, Qazvin Branch, Qazvin, Iran ' School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
Abstract: This research presents an integrated inventory-production-distribution planning model to maximise the net present value (NPV) of cash flows under fuzzy environment. The proposed model for a closed-loop supply chain (CLSC) including multiple suppliers, several manufacturing plants, and some customers is proposed. The objective function coefficients and customers' demand are assumed as the triangular fuzzy numbers. This study attempts to reduce the chain total costs including raw material procurement, production, warehousing, transportation, and reworking costs. So, the aim of this research is to determine the order quantity of raw material and production quantity of product, such that the NPV is maximised. The key feature of this work is presenting a normative framework based on the fuzzy decision-making approach to solve the production-distribution programming problems using NPV of cash flows for a three-echelon CLSC under uncertain/unknown environment. Moreover, a new solution method based on diffuzification by linear programming (LP) method is developed. At the end, performance of the proposed approach is examined using a hypothetical numerical example and also findings of the proposed model are discussed.
Keywords: inventory planning; production-distribution planning; closed-loop supply chains; CLSC; net present value; NPV; fuzzy sets; fuzzy logic; cash flows; supply chain management; SCM; inventory management; triangular fuzzy numbers; order quantity; raw materials; production quantity; linear programming.
International Journal of Inventory Research, 2016 Vol.3 No.1, pp.31 - 48
Received: 19 Jan 2016
Accepted: 13 Feb 2016
Published online: 30 Jun 2016 *