Optimizing an inventory model with fuzzy demand, backordering, and discount using a hybrid imperialist competitive algorithm

Applied Mathematical Modelling

Volumn 40, Issue 15-16, 2016, Pages 7318-7335

  Sadeghi, Javad ^a   Mousavi, Seyed Mohsen ^a,b   Niaki, Seyed Taghi Akhavan ^c  

^a ISLAMIC AZAD UNIVERSITY   (Iran)

^b UNIVERSITY OF MALAYA   (Malaysia)

^c SHARIF UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

Back order; Discount; Fuzzy demand; Hybrid imperialist competitive algorithm (HICA); Sensitivity analyses; Vendor managed inventory (VMI)

Indexed keywords

ALGORITHMS; COSTS; FUZZY SETS; HEURISTIC ALGORITHMS; SALES; SENSITIVITY ANALYSIS; SUPPLY CHAIN MANAGEMENT; SUPPLY CHAINS;

BACK ORDER; DISCOUNT; FUZZY DEMAND; IMPERIALIST COMPETITIVE ALGORITHMS; VENDOR MANAGED INVENTORY;

OPTIMIZATION;

EID: 84979461248     PISSN: 0307904X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apm.2016.03.013     Document Type: Article

References (60)

1. [1] Simchi-Levi, D., Kaminsky, P., Simchi-Levi, E., Shankar, R., Designing and Managing the Supply Chain: Concepts, Strategies and Case Studies. 3 ed., 2007, McGraw-Hill, New York.
2. [2] Disney, S.M., Towill, D.R., The effect of vendor managed inventory (VMI) dynamics on the Bullwhip ein supply chains. Int. J. Production Econ. 85 (2003), 199–215.
3. [3] Elvander, M.S., Sarpola, S., Mattsson, S.-A., Framework for characterizing the design of VMI systems. Int. J. Phys. Distrib. Logistics Manag. 37 (2007), 782–798.
4. [4] Borade, A.B., Bansod, S.V., Study of vendor-managed inventory practices in Indian industries. J. Manufacturing Technol. Manag. 21 (2010), 1013–1038.
5. [5] Pentico, D.W., Drake, M.J., A survey of deterministic models for the EOQ and EPQ with partial backordering. Eur. J. Operational Res. 214 (2011), 179–198.
6. [6] Yao, Y., Evers, P.T., Dresner, M.E., Supply chain integration in vendor-managed inventory. Decision Support Syst. 43 (2007), 663–674.
7. [7] Darwish, M.A., Odah, O.M., Vendor managed inventory model for single-vendor multi-retailer supply chains. Eur. J. Operational Res. 204 (2010), 473–484.
8. [8] Pasandideh, S.H.R., Niaki, S.T.A., Nia, A.R., A genetic algorithm for vendor managed inventory control system of multi-product multi-constraint economic order quantity model. Expert Syst. Appl. 38 (2011), 2708–2716.
9. [9] Cárdenas-Barrón, L.E., Treviño-Garza, G., Wee, H.M., A simple and better algorithm to solve the vendor managed inventory control system of multi-product multi-constraint economic order quantity model. Expert Syst. Appl. 39 (2012), 3888–3895.
10. [10] Sadeghi, J., Sadeghi, A., Saidi-Mehrabad, M., A parameter-tuned genetic algorithm for vendor managed inventory model for a case single-vendor single-retailer with multi-product and multi-constraint. J. Optim. Indus. Eng. 4 (2011), 57–67.
11. [11] Roozbeh Nia, A., Hemmati Far, M., Akhavan Niaki, S.T., A fuzzy vendor managed inventory of multi-item economic order quantity model under shortage: An ant colony optimization algorithm. Int. J. Production Econ. 155 (2014), 259–271.
12. [12] Hariga, M., Gumus, M., Daghfous, A., Goyal, S.K., A vendor managed inventory model under contractual storage agreement. Comput. Oper. Res. 40 (2013), 2138–2144.
13. [13] Sadeghi, J., Mousavi, S.M., Niaki, S.T.A., Sadeghi, S., Optimizing a multi-vendor multi-retailer vendor managed inventory problem: two tuned meta-heuristic algorithms. Knowl.-Based Syst. 50 (2013), 159–170.
14. [14] Sadjadi, S.J., Zokaee, S., Dabiri, N., A single-vendor single-buyer joint economic lot size model subject to budget constraints. The Int. J. Adv. Manufacturing Technol. 70 (2014), 1699–1707 2014/02/01.
15. [15] Amid, A., Ghodsypour, S.H., O'Brien, C., A weighted additive fuzzy multiobjective model for the supplier selection problem under price breaks in a supply chain. Int. J. Production Econ. 121 (2009), 323–332.
16. [16] Yu, Y., Huang, G.Q., Nash game model for optimizing market strategies, configuration of platform products in a vendor managed inventory (VMI) supply chain for a product family. Eur. J. Operational Res. 206 (2010), 361–373.
17. [17] Mousavi, S.M., Hajipour, V., Niaki, S.T.A., Alikar, N., Optimizing multi-item multi-period inventory control system with discounted cash flow and inflation: two calibrated meta-heuristic algorithms. Appl. Math. Model. 37 (2013), 2241–2256.
18. [18] Duan, Y., Luo, J., Huo, J., Buyer-vendor inventory coordination with quantity discount incentive for fixed lifetime product. Int. J. Prod. Econ. 128 (2010), 351–357.
19. [19] Tong, A., Dao-zhi, Z., A supply chain model of vendor managed inventory with fuzzy demand. presented at the International Conference on System Science, Engineering Design and Manufacturing Informatization (ICSEM), Yichang, China, 2010.
20. [20] Kristianto, Y., Helo, P., Jiao, J., Sandhu, M., Adaptive fuzzy vendor managed inventory control for mitigating the Bullwhip effect in supply chains. Eur. J. Operational Res. 216 (2012), 346–355.
21. [21] Mousavi, S.M., Niaki, S.T.A., Capacitated location allocation problem with stochastic location and fuzzy demand: a hybrid algorithm. Appl. Mathem. Model. 37 (2013), 5109–5119.
22. [22] Nachiappan, S.P., Jawahar, N., A genetic algorithm for optimal operating parameters of VMI system in a two-echelon supply chain. Eur. J. Oper. Res. 182 (2007), 1433–1452.
23. [23] Lin, K.-P., Chang, P.-T., Hung, K.-C., Pai, P.-F., A simulation of vendor managed inventory dynamics using fuzzy arithmetic operations with genetic algorithms. Expert Syst. Appl. 37 (2010), 2571–2579.
24. [24] Sue-Ann, G., Ponnambalam, S.G., Jawahar, N., Evolutionary algorithms for optimal operating parameters of vendor managed inventory systems in a two-echelon supply chain. Adv. Eng. Softw. 52 (2012), 47–54.
25. [25] Coello, C.A.C., Cortés, N.C., Hybridizing a genetic algorithm with an artificial immune system for global optimization. Eng. Optim. 36 (2004/10/01), 607–634.
26. [26] Yu, Y., Hong, Z., Zhang, L.L., Liang, L., Chu, C., Optimal selection of retailers for a manufacturing vendor in a vendor managed inventory system. Eur. J. Oper. Res. 225 (2013), 273–284.
27. [27] Esmaeili Aliabadi, D., Kaazemi, A., Pourghannad, B., A two-level GA to solve an integrated multi-item supplier selection model. Appl. Math. Comput. 219 (2013), 7600–7615.
28. [28] Sadeghi, J., Sadeghi, S., Niaki, S.T.A., A hybrid vendor managed inventory and redundancy allocation optimization problem in supply chain management: An NSGA-II with tuned parameters. Comput. Oper. Res. 41 (2014), 53–64.
29. [29] Atashpaz-Gargari, E., Lucas, C., Imperialist competitive algorithm: An algorithm for optimization inspired by imperialistic competition. Evolutionary Computation, Singapore, 2007, 4661–4667.
30. [30] Bigdeli, N., Afshar, K., Gazafroudi, A.S., Ramandi, M.Y., A comparative study of optimal hybrid methods for wind power prediction in wind farm of Alberta, Canada. Renewable Sustainable Energy Rev. 27 (2013), 20–29.
31. [31] Niknam, T., Taherian Fard, E., Pourjafarian, N., Rousta, A., An efficient hybrid algorithm based on modified imperialist competitive algorithm and K-means for data clustering. Eng. Appl. Artif. Intell. 24 (2011), 306–317.
32. [32] Mohammadi, M., Jolai, F., Rostami, H., An M/M/c queue model for hub covering location problem. Math. Comput. Model. 54 (2011), 2623–2638.
33. [33] Afonso, L.D., Mariani, V.C., dos Santos Coelho, L., Modified imperialist competitive algorithm based on attraction and repulsion concepts for reliability-redundancy optimization. Expert Syst. Appl. 40 (2013), 3794–3802.
34. [34] Idoumghar, L., Chérin, N., Siarry, P., Roche, R., Miraoui, A., Hybrid ICA–PSO algorithm for continuous optimization. Appl. Math. Comput. 219 (2013), 11149–11170.
35. [35] Winiczenko, R., Salat, R., Awtoniuk, M., Estimation of tensile strength of ductile iron friction welded joints using hybrid intelligent methods. Trans. Nonferrous Metals Society China 23 (2013), 385–391.
36. [36] Goldansaz, S.M., Jolai, F., Zahedi Anaraki, A.H., A hybrid imperialist competitive algorithm for minimizing makespan in a multi-processor open shop. Appl. Math. Model. 37 (2013), 9603–9616.
37. [37] Hill, R.M., The optimal production and shipment policy for the single-vendor single-buyer integrated production-inventory model. Int. J. Production Res. 37 (1999), 2463–2475.
38. [38] Braglia, M., Zavanella, L., Modelling an industrial strategy for inventory management in supply chains: the ‘consignment stock’ case. Int. J. Production Res. 41 (2003), 3793–3808.
39. [39] Zavanella, L., Zanoni, S., A one-vendor multi-buyer integrated production-inventory model: the consignment stock case. Int. J. Prod. Econ. 118 (2009), 225–232.
40. [40] Hariga, M.A., Al-Ahmari, A., An integrated retail space allocation and lot sizing models under vendor managed inventory and consignment stock arrangements. Comput. Indus. Eng. 64 (2013), 45–55.
41. [41] Tersine, R.J., Principles of Inventory and Materials Management. 4 ed., 1993, Prentice Hall, New Jersey.
42. [42] Chakrabortty, S., Pal, M., Nayak, P.K., Intuitionistic fuzzy optimization technique for Pareto optimal solution of manufacturing inventory models with shortages. Eur. J. Oper. Res. 228 (7/16/2013), 381–387.
43. [43] Lee, H.-M., Yao, J.-S., Economic production quantity for fuzzy demand quantity, and fuzzy production quantity. Eur. J. Oper. Res. 109 (1998), 203–211.
44. [44] Zanoni, S., Jaber, M.Y., Zavanella, L.E., Vendor managed inventory (VMI) with consignment considering learning and forgetting effects. Int. J. Production Econ. 140 (2012), 721–730.
45. [45] Peng, T., Jian, M., Dong-Mo, Z., Non-linear integer programming by Darwin and Boltzmann mixed strategy. Eur. J. Operational Res. 105 (1998), 224–235.
46. [46] Ross, T.J., Fuzzy Logic with Engineering Applications. second ed., 2004, Wiley, New Jersey.
47. [47] Blum, C., Puchinger, J., Raidl, G.R., Roli, A., Hybrid metaheuristics in combinatorial optimization: a survey. Appl. Soft Computi. 11 (2011), 4135–4151.
48. [48] Takao, Y., Mitsuo, G., Yin-Xiu, L., Genetic algorithm for non-linear mixed integer programming problems and its applications. Comput. Indus. Eng. 30 (1996), 905–917.
49. [49] Shi, Y., Eberhart, R., A modified particle swarm optimizer. Proceedings of IEEE International Conference on Evolutionary Computation, Anchorage, Alaska, 1998, 69–73.
50. [50] Gen, M., Cheng, R., Genetic Algorithms and Engineering Design. 1 ed., 2000, Wiley, New York.
51. [51] J. Sadeghi, S.M. Mousavi, S.T.A. Niaki, S. Sadeghi, Optimizing a multi-vendor multi-retailer vendor managed inventory problem: two tuned meta-heuristic algorithms, Knowl.-Based Syst.
52. [52] Kennedy, J., Eberhart, R., Particle swarm optimization. Proceedings of IEEE International Conference on Neural Networks, Perth, WA, Australia, 1995, 1942–1948.
53. [53] Clerc, M., Particle Swarm Optimization. 2006, ISTE Ltd, London.
54. [54] Kirkpatrick, S., Gelatt, C.D., Vecchi, M.P., Optimization by simulated annealing. Science 220 (May 13, 1983), 671–680.
55. [55] Černý, V., Thermodynamical approach to the traveling salesman problem: An efficient simulation algorithm. J. Optim. Theory Appl. 45 (1985/01/01), 41–51.
56. [56] Gupta, R.K., Bhunia, A.K., Goyal, S.K., An application of genetic algorithm in solving an inventory model with advance payment and interval valued inventory costs. Math. Comput. Model. 49 (2009), 893–905.
57. [57] Yang, W., Chan, F.T.S., Kumar, V., Optimizing replenishment polices using genetic algorithm for single-warehouse multi-retailer system. Expert Syst. Appl. 39 (2012), 3081–3086.
58. [58] Hwang, C.L., Yoon, K., Multiple Attribute Decision Making: Methods and Applications: A State-of-the-Art Survey. 1981, Springer-Verlag.
59. [59] Yoon, K.P., Hwang, C.L., Multiple Attribute Decision Making: an Introduction. 1995, SAGE Publications.
60. [60] Shahvari, O., Salmasi, N., Logendran, R., Abbasi, B., An efficient tabu search algorithm for flexible flow shop sequence-dependent group scheduling problems. Int. J. Production Res. 50 (2012), 4237–4254.