# zbMATH — the first resource for mathematics

Optimisation of integrated reverse logistics networks with different product recovery routes. (English) Zbl 1338.90031
Summary: The awareness of importance of product recovery has grown swiftly in the past few decades. This paper focuses on a problem of inventory control and production planning optimisation of a generic type of an integrated Reverse Logistics (RL) network which consists of a traditional forward production route, two alternative recovery routes, including repair and remanufacturing and a disposal route. It is assumed that demand and return quantities are uncertain. A quality level is assigned to each of the returned products. Due to uncertainty in the return quantity, quantity of returned products of a certain quality level is uncertain too. The uncertainties are modelled using fuzzy trapezoidal numbers. Quality thresholds are used to segregate the returned products into repair, remanufacturing or disposal routes. A two phase fuzzy mixed integer optimisation algorithm is developed to provide a solution to the inventory control and production planning problem. In Phase 1, uncertainties in quantity of product returns and quality of returns are considered to calculate the quantities to be sent to different recovery routes. These outputs are inputs into Phase 2 which generates decisions on component procurement, production, repair and disassembly. Finally, numerical experiments and sensitivity analysis are carried out to better understand the effects of quality of returns and RL network parameters on the network performance. These parameters include quantity of returned products, unit repair costs, unit production cost, setup costs and unit disposal cost.

##### MSC:
 90B05 Inventory, storage, reservoirs 90B06 Transportation, logistics and supply chain management 90C70 Fuzzy and other nonstochastic uncertainty mathematical programming 90B10 Deterministic network models in operations research
Full Text:
##### References:
 [1] Aras, N.; Boyaci, T.; Verter, V., The effect of categorizing returned products in remanufacturing, IIE Transactions (Institute of Industrial Engineers), 36, 4, 319-331, (2004) [2] Behret, H.; Korugan, A., Performance analysis of a hybrid system under quality impact of returns, Computers and Industrial Engineering, 56, 2, 507-520, (2009) [3] Cadenas, J.; Verdegay, J., A primer on fuzzy optimization models and methods, Iranian Journal of Fuzzy Systems, 3, 1, 1-21, (2006) · Zbl 1160.90712 [4] Das, K.; Chowdhury, A. H., Designing a reverse logistics network for optimal collection, recovery and quality-based product-mix planning, International Journal of Production Economics, 135, 1, 209-221, (2012) [5] Das, D.; Dutta, P., A system dynamics framework for integrated reverse supply chain with three way recovery and product exchange policy, Computers and Industrial Engineering, 66, 4, 720-733, (2013) [6] Dobos, I.; Richter, K., A production/recycling model with quality consideration, International Journal of Production Economics, 104, 2, 571-579, (2006) [7] El Saadany, A.; Jaber, M., A production/remanufacturing inventory model with price and quality dependant return rate, Computers and Industrial Engineering, 58, 3, 352-362, (2010) [8] Faccio, M.; Persona, A.; Sgarbossa, F.; Zanin, G., Sustainable SC through the complete reprocessing of end-of-life products by manufacturers: A traditional versus social responsibility company perspective, European Journal of Operational Research, 233, 2, 359-373, (2014) · Zbl 1305.90056 [9] Fleischmann, M.; Bloemhof-Ruwaard, J. M.; Dekker, R.; Van Der Laan, E.; Van Nunen, J. A.E. E.; Van Wassenhove, L. N., Quantitative models for reverse logistics: A review, European Journal of Operational Research, 103, 1, 1-17, (1997) · Zbl 0920.90057 [10] Galbreth, M.; Blackburn, J., Optimal acquisition and sorting policies for remanufacturing, Production and Operations Management, 15, 3, 384-392, (2006) [11] Guide, V. D.R.; Muyldermans, L.; Van Wassenhove, L. N., Hewlett-packard company unlocks the value potential from time-sensitive returns, Interfaces, 35, 4, 281-293, (2005) [12] Guo, S.; Aydin, G.; Souza, G. C., Dismantle or remanufacture?, European Journal of Operational Research, 233, 3, 580-583, (2014) · Zbl 1339.90052 [13] Herrera, F.; Verdegay, J., Three models of fuzzy integer linear programming, European Journal of Operational Research, 83, 3, 581-593, (1995) · Zbl 0899.90160 [14] Ilgin, M.; Gupta, S., Environmentally conscious manufacturing and product recovery (ecmpro): A review of the state of the art, Journal of Environmental Management, 91, 3, 563-591, (2010) [15] Inderfurth, K., Impact of uncertainties on recovery behavior in a remanufacturing environment. A numerical analysis, International Journal of Physical Distribution and Logistics Management, 35, 5, 318-336, (2005) [16] Inuiguchi, M.; Ramik, J., Possibilistic linear programming: A brief review of fuzzy mathematical programming and a comparison with stochastic programming in portfolio selection problem, Fuzzy Sets and Systems, 111, 1, 3-28, (2000) · Zbl 0938.90074 [17] Jayaraman, V., Production planning for closed-loop supply chains with product recovery and reuse: an analytical approach, International Journal of Production Research, 44, 5, 981-998, (2006) · Zbl 1095.90533 [18] Lebreton, B.; Tuma, A., A quantitative approach to assessing the profitability of car and truck tire remanufacturing, International Journal of Production Economics, 104, 2, 639-652, (2006) [19] Mahapatra, S.; Pal, R.; Narasimhan, R., Hybrid (re)manufacturing: manufacturing and operational implications, International Journal of Production Research, 50, 14, 3786-3808, (2012) [20] Mitra, S., Revenue management for remanufactured products, Omega, 35, 5, 553-562, (2007) [21] Mukhopadhyay, S.; Ma, H., Joint procurement and production decisions in remanufacturing under quality and demand uncertainty, International Journal of Production Economics, 120, 1, 5-17, (2009) [22] Nenes, G.; Nikolaidis, Y., A multi-period model for managing used product returns, International Journal of Production Research, 50, 5, 1360-1376, (2012) [23] Nenes, G.; Panagiotidou, S.; Dekker, R., Inventory control policies for inspection and remanufacturing of returns: A case study, International Journal of Production Economics, 125, 2, 300-312, (2010) [24] Petrovic, D.; Xie, Y.; Burnham, K.; Petrovic, R., Coordinated control of distribution supply chains in the presence of fuzzy customer demand, European Journal of Operational Research, 185, 1, 146-158, (2008) · Zbl 1146.90321 [25] Souza, G.; Ketzenberg, M. E.; Guide, V. D.R., Capacitated remanufacturing with service level constraintsmidast, Production and Operations Management, 11, September 2000, (2002) [26] Yoo, S. H.; Kim, D.; Park, M.-S., Lot sizing and quality investment with quality cost analyses for imperfect production and inspection processes with commercial return, International Journal of Production Economics, 140, 2, 922-933, (2012) [27] Zadeh, L., The concept of a linguistic variable and its application to approximate reasoning - I, Information Sciences, 8, 3, 199-249, (1975) · Zbl 0397.68071 [28] Zikopoulos, C.; Tagaras, G., Impact of uncertainty in the quality of returns on the profitability of a single-period refurbishing operation, European Journal of Operational Research, 182, 1, 205-225, (2007) · Zbl 1128.90008 [29] Zimmermann, H., Fuzzy set theory - and its applications, (2001), Springer Netherlands, Dordrecht
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.