JOURNAL BROWSE
Search
Advanced SearchSearch Tips
Pareto-Based Multi-Objective Optimization for Two-Block Class-Based Storage Warehouse Design
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
Pareto-Based Multi-Objective Optimization for Two-Block Class-Based Storage Warehouse Design
Sooksaksun, Natanaree;
  PDF(new window)
 Abstract
This research proposes a Pareto-based multi-objective optimization approach to class-based storage warehouse design, considering a two-block warehouse that operates under the class-based storage policy in a low-level, picker-to-part and narrow aisle warehousing system. A mathematical model is formulated to determine the number of aisles, the length of aisle and the partial length of each pick aisle to allocate to each product class that minimizes the travel distance and maximizes the usable storage space. A solution approach based on multiple objective particle swarm optimization is proposed to find the Pareto front of the problems. Numerical examples are given to show how to apply the proposed algorithm. The results from the examples show that the proposed algorithm can provide design alternatives to conflicting warehouse design decisions.
 Keywords
Warehouse Design;Multi-Objective;Two-Block Warehouse;Class-Based Storage Policy;
 Language
English
 Cited by
 References
1.
Caron, F., Marchet, G., and Perego, A. (1998), Routing policies and COI-based storage policies in pickerto- part systems, International Journal of Production Research, 36(3), 713-732. crossref(new window)

2.
Caron, F., Marchet, G., and Perego, A. (2000), Layout design in manual picking systems: a simulation approach, Integrated Manufacturing System, 11(2), 94-104. crossref(new window)

3.
Garcia-Diaz, A. and Smith, J. M. (2008), Facilities Planning and Design, Pearson Prentice Hall, Upper Saddle River, NJ.

4.
Gu, J., Goetschalckx, M., and McGinnis, L. F. (2007), Research on warehouse operation: a comprehensive review, European Journal of Operational Research, 177(1), 1-21. crossref(new window)

5.
Gu, J., Goetschalckx, M., and McGinnis, L. F. (2010), Research on warehouse design and performance evaluation: a comprehensive review, European Journal of Operational Research, 203(3), 539-549. crossref(new window)

6.
Hwang, H., Oh, Y. H., and Lee, Y. K. (2004), An evaluation of routing policies for order-picking operations in low-level picker-to-part system, International Journal of Production Research, 42(18), 3873- 3889. crossref(new window)

7.
Kachitvichyanukul, V. and Nguyen, P. B. (2010), Evolutionary strategies to find pareto fronts in multiobjective problems, In: Walters, L. P. (ed.), Applications of Swarm Intelligence, Nova Science Publishers, New York, NY.

8.
Lai, K. K., Xue, J., and Zhang, G. (2002), Layout design for a paper reel warehouse: A two-stage heuristic approach, International Journal of Production Economics, 75(3), 231-243. crossref(new window)

9.
Larson, T. N., March, H., and Kusiak, A. (1997), A heuristic approach to warehouse layout with classbased storage, IIE Transactions, 29(4), 337-348.

10.
Le-Duc, T. and De Koster, R. B. M. (2005), Travel distance estimation and storage zone optimization in a 2-block class-based storage strategy warehouse, International Journal of Production Research, 47(13), 3561-3581.

11.
Li, M., Chen, X., and Liu, C. (2008), Pareto and niche genetic algorithm for storage location assignment optimization problem, Proceedings of the 3rd International Conference on Innovative Computing Information and Control, Dalian, China, 465.

12.
Nguyen, S. and Kachitvichyanukul, V. (2010), Movement strategies for multi-objective particle swarm optimization, International Journal of Applied Metaheuristic Computing, 1(3), 59-79. crossref(new window)

13.
Nguyen, S., Ai, T. J., and Kachitvichyanukul, V. (2010), Object Library for Evolutionary Techniques ET-Lib: User's Guide, High Performance Computing Group, Asian Institute of Technology, Thailand.

14.
Onut, S., Tuzkaya, U. R., and Dogac, B. (2008), A particle swarm optimization algorithm for the multiple- level warehouse layout design problem, Computers and Industrial Engineering, 54(4), 783-799. crossref(new window)

15.
Park, Y. H. and Webster, D. B. (1989a), Modelling of three-dimensional warehouse systems, International Journal of Production Research, 27(6), 985- 1003. crossref(new window)

16.
Park, Y. H. and Webster, D. B. (1989b), Design of classbased storage racks for minimizing travel time in a three-dimensional storage system, International Journal of Production Research, 27(9), 1589-1601. crossref(new window)

17.
Petersen II, C. G. (1997), An evaluation of order picking routeing policies, International Journal of Operations and Production Management, 17(11), 1098- 1111. crossref(new window)

18.
Petersen II, C. G. (1999), The impact of routing and storage policies on warehouse efficiency, International Journal of Operations and Production Management, 19(10), 1053-1064. crossref(new window)

19.
Petersen, C. G., Aase, G. R., and Heiser, D. R. (2004), Improving order-picking performance through the implementation of class-based storage, International Journal of Physical Distribution and Logistics Management, 34(7), 534-544. crossref(new window)

20.
Poulos, P. N., Rigatos, G. G., Tzafestas, S. G., and Koukos, A. K. (2001), A Pareto-optimal genetic algorithm for warehouse multi-objective optimization, Engineering Applications of Artificial Intelligence, 14(6), 737-749. crossref(new window)

21.
Sooksaksun, N. and Kachitvichyanukul, V. (2010), Particle swarm optimization for warehouse design problem, Proceedings of the 11th Asia Pacific Industrial Engineering and Management Systems Conference, Melaka, Malaysia.

22.
Tompkins, J. A., White, J. A., Bozer, Y. A., Frazelle, E. H., Tanchoco, J. M. A., and Trevino, J. (1996), Facilities Planning (2nd ed.), Wiley, New York, NY.

23.
Van den Berg, J. P. (1999), A literature survey on planning and control of warehousing systems, IIE Transactions, 31(8), 751-762.