Economical impact of RFID implementation in remanufacturing: a Chaos-based Interactive Artificial Bee Colony approach

Journal of Intelligent Manufacturing

Volumn 26, Issue 4, 2015, Pages 815-830

  Kumar, Vishwa V ^a   Liou, F W ^a   Balakrishnan, S N ^a   Kumar, Vikas ^b  

^a University of Missouri Rolla   (United States)

^b DUBLIN CITY UNIVERSITY   (Ireland)

Author keywords

Artificial Bee colony; Particle swarm optimization; Remanufacturing; RFID

Indexed keywords

BALLOONS; COMPENSATION (PERSONNEL); ECONOMIC AND SOCIAL EFFECTS; ECONOMICS; EVOLUTIONARY ALGORITHMS; INTERACTIVE COMPUTER SYSTEMS; LOGISTICS; OPTIMIZATION; PARTICLE SWARM OPTIMIZATION (PSO); REAL TIME SYSTEMS; WAGES;

ARTIFICIAL BEE COLONIES; ECONOMICAL IMPACT; ECONOMICALLY VIABLE; FINANCIAL INVESTMENTS; OPTIMAL PERFORMANCE; RADIO FREQUENCY IDENTIFICATION TECHNOLOGY; REMANUFACTURING; REVERSE LOGISTICS;

RADIO FREQUENCY IDENTIFICATION (RFID);

EID: 84937944766     PISSN: 09565515     EISSN: 15728145     Source Type: Journal    
DOI: 10.1007/s10845-013-0836-9     Document Type: Article

References (42)

1. Blanc, I. L., Krieken, M. V., Krikke, H., & Fleuren, H. (2006). Vehicle routing concepts in the closed-loop container network of ARN a case study. OR Spectrum, 28, 53–71.
2. Bottani, E., & Rizzi, A. (2008). Economical assessment of the impact of RFID technology and EPC system on the fast-moving consumer goods supply chain. International Journal of Production Economics, 112(2), 548–569.
3. Bu, X., & Xu, S. (2008). The profit model in reverse logistics under the different environmental factors. In IEEE International conference on service operations and logistics (pp. 1215–1220). Beijing, China
4. Charter, M., & Gray, C. (2008). Remanufacturing and product design. International Journal of Product Development, 6(3/4), 375–392.
5. Doh, H.-H., & Lee, D.-H. (2010). Generic production planning model for remanufacturing systems. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 224(1), 159–168.
6. Dowlatshahi, S. (2012). A framework for the role of warehousing in Reverse Logistics. International Journal of Production Research, 50(5), 1265–1277.
7. Franke, C., Basdere, B., Ciupek, V., & Seliger, S. (2006). Remanufacturing of mobile phones-capacity, program and facility adaptation planning. The International Journal of Management Science, 34, 562–570.
8. Hong, I. H., Assavapokee, T., Ammons, J., Boelkins, C., Gilliam, K., Oudit, D., et al. (2006). Planning the e-scrap reverse production system under uncertainty in the state of Georgia: A case study. IEEE Transactions on Electronics Packaging Manufacturing, 29(3), 150–162
9. Jayaraman, V. (2006). Production planning for closed-loop supply chains with product recovery and reuse: An analytical approach. International Journal of Production Research, 44(5), 981–998.
10. Jung, K. S., & Hwang, H. (2011). Competition and cooperation in a remanufacturing system with take-back requirement. Journal of Intelligence Manufacturing, 22, 427–433.
11. Karaboga D., (2005). An idea based on honey bee swarm for numerical optimization. Technical report-TR06, Erciyes University, Engineering Faculty, Computer Engineering Department.
12. Kim, M.-C., Kim, C. O., Hong, S. R., & Kwon, I. H. (2008). Forward-backward analysis of RFID-enabled supply chain using fuzzy cognitive map and genetic algorithm. Expert Systems with Applications, 35, 1166–1176.
13. Ko, H. J., & Evans, G. W. (2007). A genetic algorithm-based heuristic for the dynamic integrated forward/reverse logistics network for 3PLs. Computers & Operations Research, 34(2), 346–366.
14. Konstantaras, I., & Papachristos, S. (2007). Optimal policy and holding cost stability regions in a periodic review inventory system with manufacturing and remanufacturing options. European Journal of Operational Research, 178, 433–448.
15. Kumar, V. V., Chan, F. T. S., Mishra, N., & Kumar, V. (2010). Environmental integrated closed loop logistics model: An artificial bee colony approach. In 8th International conference on SCMIS, 6–8 October 2010, Hong Kong.
16. Kumar, V. V., Pandey, M. K., Tiwari, M. K., & Ben-Arieh, D. (2010). Simultaneous optimization of parts and operations sequences in SSMS: A chaos embedded Taguchi particle swarm optimization approach. Journal of Intelligent Manufacturing, 21(4), 335–353.
17. Kumar, V. V., Tripathi, M., Pandey, M. K., & Tiwari, M. K. (2009). Physical programming and conjoint analysis-based redundancy allocation in multistate systems: A Taguchi embedded algorithm selection and control (TAS &C) approach. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 223(3), 215–232.
18. Kumar, R., Tiwari, M. K., & Shankar, R. (2003). Scheduling of flexible manufacturing systems: An ant colony optimization approach. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 217(10), 1443–1453.
19. Kumar, V. V., & Chan, F. T. S. (2011). A superiority search and optimisation algorithm to solve RFID and an environmental factor embedded closed loop logistics model. International Journal of Production Research, 49(16), 4807–4831.
20. Lazzús, J. A. (2013). Hybrid particle swarm-ant colony algorithm to describe the phase equilibrium of systems containing supercritical fluids with ionic liquids. Communications in Computational Physics, 14(1), 107–125.
21. Lee D. H., Bian W. & Dong M. (2008). Multiproduct distribution network design of third-party logistics providers with reverse logistics operations. Journal of the Transportation Research Board, 2008(4), 26–33.
22. Lee, C. K. M., & Chan, T. M. (2009). Development of RFID-based reverse logistics system. Expert Systems with Applications, 36, 9299–9307.
23. Lee, D. H., & Dong, M. (2009). Dynamic network design for reverse logistics operations under uncertainty. Transportation Research Part E, 45, 61–71.
24. Luo, C. Z., & Shao, H. H. (2000). Evolutionary algorithms with chaotic perturbations. Control Decision, 15, 557–560.
25. Naeem, M. A., Dias, D. J., Tibrewal, R., Chang, P. C., & Tiwari, M. K. (2013). Production planning optimization for manufacturing and remanufacturing system in stochastic environment. Journal Intelligence Manufacturing, 24, 717–728.
26. Ngai, E. W. T., Cheng, T. C. E., Au, S., & Lai, K. H. (2007). Mobile commerce integrated with RFID technology in a container depot. Decision Support Systems, 43(1), 62–76.
27. Pan, Z., Tang, J., & Ou, L. (2009). capacitated dynamic lot sizing problems in closed-loop supply chain. European Journal of Operational Research, 198, 810–821.
28. Parker, T. S., & Chua, L. O. (1989). Practical numerical algorithms for chaotic system. Berlin, Germany: Springer.
29. Pigni, F., & Ugazio, E. (2009). Measuring RFId benefits in supply chains. In Proceedings of the fifteenth Americas conference on information systems, San Francisco, California.
30. Pineyro, P., & Viera, O. (2010). The economic lot-sizing problem with remanufacturing and one-way substitution. International Journal of Production Economics, 124, 482–488.
31. Prakash, A., Tiwari, M. K., & Shankar, R. (2008). Optimal job sequence determination and operation machine allocation in flexible manufacturing systems: An approach using adaptive hierarchical ant colony algorithm. Journal of Intelligent Manufacturing, 19(2), 161–173.
32. Salema, M. I. G., Barbosa-Povoa, A. P., & Novais, A. Q. (2006). An optimization model for the design of a capacitated multi-product reverse logistics network with uncertainty. European Journal of Operation Research, 179(3), 1063–1077.
33. Schultmann, F., Zumkeller, M., & Rentz, O. (2006). Modeling reverse logistic tasks within closed-loop supply chains: An example from the automotive industry. European Journal of Operational Research, 171(3), 1033–1050.
34. Soleymanpour, D. M., Vrat, P., & Shankar, R. (2003). Ant colony optimization algorithm to the inter-cell layout problem in cellular, manufacturing. European Journal of Operational Research, 157(3), 592–606.
35. Stanfield, P. M., King, R. E., & Hodgson, T. J. (2006). Determining sequence and ready times in a remanufacturing system. IIE Transactions, 38, 597–607.
36. Tsai, P. W., Pan, J.-S., Liao, B.-Y., & Chu, S.-C. (2009). Enhanced artificial bee colony optimization. International Journal of Innovative Computing, Information and Control, 5(12), 5081–5092
37. Ustundag, A., & Tanyas, M. (2009). The impacts of radio frequency identification (RFID) technology on supply chain costs. Transportation Research Part E: Logistics and Transportation Review, 45(1), 29–38.
38. Veeramani, D., Tang, J., & Gutierrez, A. (2008). A framework for assessing the value of RFID implementation by tier-one suppliers to major retailers. Journal of Theoretical and Applied Electronic Commerce Research, 3(1), 55–70.
39. Wang, I. L., & Yang, W. C. (2007). Fast heuristics for designing integrated e-waste reverse logistics networks. IEEE Transactions on Electronics Packaging Manufacturing, 30(2), 147–154.
40. Yadav, S. R., Dashora, Y., Shankar, R., & Tiwari, M. K. (2008). An interactive particle swarm optimization technique for selecting a product family and designing its supply. International Journal of Intelligent Systems Technologies and Applications, 31(3–4), 168–186.
41. Yang, L., & Chen, T. (2002). Application of chaos in genetic algorithms. Communication Theoretical Physics, 38, 168–172.
42. Yuan, X. H., Yuan, Y. B., & Zhang, Y. C. (2002). A hybrid chaotic genetic algorithm for short-term hydro system scheduling. Mathematics and Compuers Simulation, 59, 319–327.