Table of Contents Author Guidelines Submit a Manuscript
Advances in Operations Research
Volume 2017, Article ID 3601217, 18 pages
https://doi.org/10.1155/2017/3601217
Research Article

Population Based Metaheuristic Algorithm Approach for Analysis of Multi-Item Multi-Period Procurement Lot Sizing Problem

Department of Mechanical Engineering, National Institute of Technology Karnataka, Surathkal, Mangalore, Karnataka, India

Correspondence should be addressed to Prasanna Kumar; ni.oc.oohay@6ramukrp

Received 20 March 2017; Revised 6 August 2017; Accepted 7 November 2017; Published 20 December 2017

Academic Editor: Paolo Gastaldo

Copyright © 2017 Prasanna Kumar et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. F. W. Harris, “How Many Parts to Make at Once,” Operations research, vol. 38, no. 6, pp. 947–950, 1990. View at Publisher · View at Google Scholar
  2. H. M. Wagner and T. M. Whitin, “Dynamic version of the economic lot size model,” Management Science, vol. 5, no. 1, pp. 89–96, 1958. View at Publisher · View at Google Scholar · View at MathSciNet
  3. K. Das, T. K. Roy, and M. Maiti, “Multi-item inventory model with quantity-dependent inventory costs and demand-dependent unit cost under imprecise objective and restrictions: a geometric programming approach,” Production Planning and Control, vol. 11, no. 8, pp. 781–788, 2000. View at Publisher · View at Google Scholar · View at Scopus
  4. G. Nenes, S. Panagiotidou, and G. Tagaras, “Inventory management of multiple items with irregular demand: a case study,” European Journal of Operational Research, vol. 205, no. 2, pp. 313–324, 2010. View at Publisher · View at Google Scholar · View at Scopus
  5. S. Panda, K. Banerjee, and M. Basu, “Determination of EOQ of multi-item inventory problems through nonlinear goal programming with penalty function,” Asia-Pacific Journal of Operational Research, vol. 22, no. 4, pp. 539–553, 2005. View at Publisher · View at Google Scholar · View at Scopus
  6. D. Kim and C. Kim, “Forecasting time series with genetic fuzzy predictor ensemble,” IEEE Transactions on Fuzzy Systems, vol. 5, no. 4, pp. 523–535, 1997. View at Publisher · View at Google Scholar · View at Scopus
  7. A. K. Maiti and M. Maiti, “Discounted multi-item inventory model via genetic algorithm with roulette wheel selection, arithmetic crossover and uniform mutation in constraints bounded domains,” International Journal of Computer Mathematics, vol. 85, no. 9, pp. 1341–1353, 2008. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  8. S. S. Sana and K. S. Chaudhuri, “A deterministic EOQ model with delays in payments and price-discount offers,” European Journal of Operational Research, vol. 184, no. 2, pp. 509–533, 2008. View at Publisher · View at Google Scholar · View at MathSciNet
  9. S. M. Mousavi, V. Hajipour, S. T. A. Niaki, and N. Alikar, “Optimizing multi-item multi-period inventory control system with discounted cash flow and inflation: Two calibrated meta-heuristic algorithms,” Applied Mathematical Modelling, vol. 37, no. 4, pp. 2241–2256, 2013. View at Publisher · View at Google Scholar · View at Scopus
  10. S. H. R. Pasandideh, S. T. A. Niaki, and N. Tokhmehchi, “A parameter-tuned genetic algorithm to optimize two-echelon continuous review inventory systems,” Expert Systems with Applications, vol. 38, no. 9, pp. 11708–11714, 2011. View at Publisher · View at Google Scholar · View at Scopus
  11. A. Colorni, M. Dorigo, and V. Maniezzo, “Distributed optimization by antcolonies,” in Proceedings of the European Conference on Artficial Life, pp. 134–142, Paris, France, 1991.
  12. J. N. Patel, “Accuracy Comparison of Various Techniques to Solve Machine Layout Problem,” International Journal of Advanced Research in Computer Science, vol. 2, no. 1, 2011. View at Google Scholar
  13. A. Narayanan, P. Robinson, and F. Sahin, “Coordinated deterministic dynamic demand lot-sizing problem: a review of models and algorithms,” Omega , vol. 37, no. 1, pp. 3–15, 2009. View at Publisher · View at Google Scholar · View at Scopus
  14. R. Roy, Society of Manufacturing Engineers, NY, USA, 1990.
  15. K. Dehnad, Quality Control, Robust Design, and the Taguchi Method, Springer US, Boston, MASS, USA, 1989. View at Publisher · View at Google Scholar
  16. D. Choudhary and R. Shankar, “Modeling and analysis of single item multi-period procurement lot-sizing problem considering rejections and late deliveries,” Computers & Industrial Engineering, vol. 61, no. 4, pp. 1318–1323, 2011. View at Publisher · View at Google Scholar · View at Scopus