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Soft Computing
Erschienen in: Soft Computing 11/2015

01.11.2015 | Methodologies and Application

Development of an optimization model for product returns using genetic algorithms and simulated annealing

verfasst von: Vahidreza Ghezavati, Niloofar Saadati Nia

Erschienen in: Soft Computing | Ausgabe 11/2015

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Abstract

Product returns have become a significant management issue and an unavoidable cost for a business. This situation made firms to consider the possibility of managing product returns in a more cost-efficient way. In this paper, we develop a mixed integer non-linear programming model of a three-stage logistics network to optimize the number and location of collection/inspection centers and recovery centers as well as collection frequency with the objective of minimizing the total costs which include the reverse logistics shipping costs and fixed costs of opening facilities. We propose two solution algorithms based on genetic algorithm (GA) and simulated annealing (SA). Numerical experiments are used to illustrate the effectiveness and efficiency of the proposed solution approaches and compare the results with the previous works.
Vorheriger Artikel Computational efficiency and universality of timed P systems with membrane creation
Nächster Artikel An improved PSO algorithm based on particle exploration for function optimization and the modeling of chaotic systems

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Literatur
Alumur SA, Nickel S, Saldanha-da-Gama F, Verter V (2012) Multi-period reverse logistics network design. Eur J Oper Res 220(1):67–78MathSciNetCrossRefMATH
Aras N, Aksen D, Tanu\(\eth \)ur AG (2008) Locating collection centers for incentive-dependent returns under a pick-up policy with capacitated vehicles. Eur J Oper Res 191(3):1223–1240
Awan H, Abdullah K, Faryad M (2008) Implementing smart antenna system using genetic algorithm and artificial immune system. In: 17th international conference on radar and wireless communications
Barros AI, Dekker R, Scholten V (1998) A two-level network for recycling sand: a case study. Eur J Oper Res 110(2):199–214CrossRefMATH
Chen G, Govindan K, Yang Z, Choi T, Jiang L (2013) Terminal appointment system design by non-stationary M(t)/Ek/c(t) queueing model and genetic algorithm. Int J Prod Econ 146:694–703CrossRef
Cheng X, Wan W, Xu X (1998) Modeling rolling batch planning as a vehicle routing problem with time windows. Comput Oper Res 25(12):1127–1136CrossRef
Daugherty PJ, Richey RG, Genchev SE, Chen H (2005) Reverse logistics: superior performance through focused resource commitments to information technology. Transp Res Part E 41(2):77–92CrossRef
Diabat A, Kannan D, Kaliyan M (2013) An optimization model for product returns using genetic algorithms and artificial immune system. Resour Conserv Recycl 74:156–169CrossRef
Fleischer MA (1995) Simulated annealing: past, present and future. In: Proceedings of the 1995 Winter Simulation Conference, pp 155–161
Fleischmann M, Beullens P, Bloemhof-ruwaard JM, Wassenhohve V (2001) The impact of product recovery on logistics network design. Prod Oper Manag 10:156–173CrossRef
Fleischmann M, Bloemhof-Ruwaard JM, Dekker R, van der Laan EA, van Nunen JAEE (1997) Quantitative models for reverse logistics: a review. Eur J Oper Res 103:1–17CrossRefMATH
Gen M, Cheng R (1997) Genetic algorithms and engineering design. Wiley, New York, pp 1–432
Gen M, Cheng R (2000) Genetic algorithms and engineering optimizations. Wiley, New York
Goldberg DE (1989) Genetic algorithms in search, optimization and machine learning. Addison-Wesley, ReadingMATH
Holland JH (1975) Adaptation in natural and artificial systems. The University of Michigan Press, Ann Arbor
Jayant A, Gupta P, Garg SK (2011) Design and simulation of reverse logistics network: a case study. In: Proceedings of the World Congress on Engineering, vol 1. pp 1–5
Jayaraman V, Guide VDR Jr, Srivastava R (1999) Closed-loop logistics model for remanufacturing. J Oper Res Soc 50(5):497–508CrossRefMATH
Jayaraman V, Patterson RA, Rolland E (2003) The design of reverse distribution networks: models and solution procedures. Eur J Oper Res 150(1):128–149MathSciNetCrossRefMATH
Ko HJ, Evans GW (2007) A genetic algorithm-based heuristic for the dynamic integrated forward/reverse logistics network for 3PLs. Comput Oper Res 34:346–366CrossRefMATH
Krikke HR, Harten A, Schuur PC (1999a) Business case Roteb: recovery strategies for monitors. Comput Ind Eng 36(4):739–757CrossRef
Lee D, Dong M (2009) Dynamic network design for reverse logistics operations under uncertainty. Transp Res Part E 45(1):61–71MathSciNetCrossRef
Lee JE, Gen M, Rhee KG (2009) Network model and optimization of reverse logistics by hybrid genetic algorithm. Comput Ind Eng 56(3):951–964CrossRef
Lieckens K, Vandaele N (2007) Reverse logistics network design: the extension towards uncertainty. Comput Oper Res 34(2):395–416CrossRefMATH
Listes OL, Dekker R (2001) Stochastic approaches for product recovery network design: a case study. Econometric Institute Report
Louwers D, Kip BJ, Peters E, Souren F, Flapper SDP (1999) A facility location alloca-tion model for reusing carpet material. Comput Ind Eng 36(4):855–869CrossRef
Lu Z, Bostel N (2007) A facility location model for logistics systems including reverse flows: the case of remanufacturing activities. Comput Oper Res 34(2):299–323MathSciNetCrossRefMATH
Michalewicz Z (1996) Genetic algorithms + data structures = evolution programs, 3rd edn. Springer, BerlinCrossRefMATH
Min H, Ko H-J (2008) The dynamic design of a reverse logistics network from the perspective of third-party logistics service providers. Int J Prod Econ 113(1):176–192CrossRef
Min H, Ko HJ, Ko CS (2006a) A genetic algorithm approach to developing the multi-echelon reverse logistics network for product returns. Omega 34(1):56–69CrossRef
Min H, Ko CS, Ko HJ (2006b) The spatial and temporal consolidation of returned products in a closed-loop supply chain network. Comput Ind Eng 51(2):309–320CrossRef
Pasandideh SHR, Niaki STA, dan Nia AR (2011) A genetic algorithm for vendor managed inventory control system of multi-product multi-constraint economic order quantity model. Expert Syst Appl 38(3):2078–2716
Pati RK, Vrat P, Kumar P (2008) A goal programming model for paper recycling system. Omega 36(3):405–17CrossRef
Pishvaee MS, Farahani RZ, Dullaert W (2010a) A memetic algorithm for bi-objective integrated forward/reverse logistics network design. Comput Oper Res 37(6):1100–1112
Pishvaee MS, Jolai F, Razmi J (2009) A stochastic optimization model for integrated forward/reverse logistics. J Manuf Syst 28(4):107–114CrossRef
Pishvaee MS, Rabbani M, Torabi SA (2011) A robust optimization approach to closed-loop supply chain network design under uncertainty. Appl Math Model 35(2):637–649
Ramezani M, Bashiri M, Tavakkoli-Moghaddam R (2012) A new multi-objective stochastic model for a forward/reverse logistic network design with responsiveness and quality level. Appl Math Model. doi:10.​1016/​j.​apm.​2012.​02.​032
Realff MJ, Ammons JC, Newton D (1999) Carpet recycling: determining the reverse production system design. Polym Plast Technol Eng 38(3):547–567CrossRef
Rogers DS, Tibben-Lembke RS (1999) Going backwards reverse logistics trend and practices. Reverse Logistics Executive Council, Pittsburgh
Romeo F, Sangiovanni-Vincentelli A (1991) A theoretical framework for simulated annealing. Algorithmica 6(1–6):302–345
Salema MIG, Barbosa-Povoa AP, Novais AQ (2007) An optimization model for the design of a capacitated multi-product reverse logistics network with uncertainty. Eur J Oper Res 179(3):1063–1077CrossRefMATH
Santos MO, Massago S, Almada-Lobo BL (2010) Infeasibility handling in genetic algorithm using nested domains for production planning. Comput Oper Res 37(6):1113–1122CrossRefMATH
Metadaten
Titel
Development of an optimization model for product returns using genetic algorithms and simulated annealing
verfasst von
Vahidreza Ghezavati
Niloofar Saadati Nia
Publikationsdatum
01.11.2015
Verlag
Springer Berlin Heidelberg
Erschienen in
Soft Computing / Ausgabe 11/2015
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-014-1465-8

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