IE interfaces (산업공학)

Korean Institute of Industrial Engineers (대한산업공학회)
권호 표지

Integrated Production-Distribution Planning for Single-Period Inventory Products Using a Hybrid Genetic Algorithm

혼성 유전알고리듬을 이용한 단일기간 재고품목의 통합 생산-분배계획 해법

  • Park, Yang-Byung (Mechanical and Industrial Systems Engineering, College of Advanced Technology, Kyung Hee University)
  • 박양병 (경희대학교 테크노공학대학 기계 산업시스템공학부)
  • Received : 20030300
  • Accepted : 20030600
  • Published : 2003.09.30
Download PDF
⟨ Previous Next ⟩

Abstract

Many firms are trying to optimize their production and distribution functions separately, but possible savings by this approach may be limited. Nowadays, it is more important to analyze these two functions simultaneously by trading off the costs associated with the whole. In this paper, I treat a production and distribution planning problem for single-period inventory products comprised of a single production facility and multiple customers, with the aim of optimally coordinating important and interrelated decisions of production sequencing and vehicle routing. Then, I propose a hybrid genetic algorithm incorporating several local optimization techniques, HGAP, for integrated production-distribution planning. Computational results on test problems show that HGAP is effective and generates substantial cost savings over Hurter and Buer's decoupled planning approach in which vehicle routing is first developed and a production sequence is consequently derived. Especially, HGAP performs better on the problems where customers are dispersed with multi-item demand than on the problems where customers are divided into several zones based on single-item demand.

Keywords

References

  1. 손현덕(2002), 매일경제, 2002. 1. 22
  2. 정성원, 장양자, 박진우 (2001), 유전알고리듬을 이용한 생산 및 배송 계획, 한국경영과학회지, 26(4), 133-141
  3. Bierwirth, C. and Mattfeld, D.C. (1999), Production Scheduling and Rescheduling with Genetic Algorithms, Evolutionary Computation, 7(1),1-17
  4. Braysy, O. and Gendreau, M. (2001), Genetic Algorithms for the Vehicle Routing Problem with Time Windows, SINTEF Report, SINTEF Applied Mathematics, Research Council of Norway
  5. Buer, M.G.V., Woodruff, D,L., and Olson, R.T. (1999), Solving the Medium Newspaper Production/Distribution Problem, European Journal of Operational Research, 115, 237-253
  6. Clarke. G. and Wright, J. (1964), Scheduling of Vehi치es from a Central Depot to a Number of Delivery Points, Operations Research, 12, 568-581
  7. Cordeau. J.F., Gendreau, M., Laporte. G., Patvin, J.Y., and Semet, F. (2002), A Guide to Vehicle Routing Heuristics, Journal of the Operational Research Society, 53(5), 512-522
  8. Erenguc. S.S., Simpson, N.C., and Vakharia, A.J. (2001), Integrated Production/Distribution Planning in Supply Chains: An Invited Review, European Journal of Operational Research, 115, 219-236
  9. Gen, M. and Cheng, R. (1997), Genetic Algorithms & Engineering Design. John Wiley& Sons, Inc
  10. Hurter, A.P. and Buer, M.G.V. (1996), The Newspaper Production/Distribution Problems, Journal of Business Logistics, 17(1), 85-107
  11. Lai, K.K. and Liu, B. (2003), A Goal Programming Model for Vehicle Routing Problems with Soft Time Windows and Its Genetic Algorithm, International Journal of Systems Science, to appear in 2003
  12. Li, Y., lp, W.H., and Wang, D.W. (1998), Genetic Algorithm Approach to Earliness and Tardiness Production Scheduling and Planning Problem, International Journal of Production Economics, 54, 65-76
  13. Mabert. V.A., and Venkatararnanan (1998), Special Research Focus on Supply Chain Linkages: Challenges for Design and Management in the 21st Century, Decision Sciences, 29(3), 537-552
  14. Michalewicz, Z. (1994), Genetic Algorithms + Data Structures = Evolution Programs, Programs, 2nd Edition, Springer-Verlag
  15. Reeves. C.R. (1995), A Genetic Algorithm for Flowshop Sequencing, Computers & Operations Research, 22(1), 5-13
  16. Sarmiento, A.M., and Nagi, R. (1999), A Review of Integrated Analysis of Production-Distribution Systems, IIE Transactions, 31, 1061-1074
  17. Schmitt L.J. and Amini, M.M. (1998), Performance Characteristics of Alternative Generic Algorithmic Approaches to TSP Using Path Representation: An Empirical Study. European Journal of Operational Research, 108, 511-170
  18. Shapiro, J.F. (1999), Chap. 23: Bottom-Up vs. Top-Down Approaches to Supply Chain Modeling, Quantitative Models for Supply Chain Management, Tayur, S., Geneshan, R., and Magazine, M. (eds), Kluwer Academic Publishers, Boston
  19. Wang, C. and Uzsoy, R.(2002), A Genetic Algorithm to Minimize Maximum Lateness on a Batch Processing Machine, Computers & Operations Research, 29, 1621-1640