Applying Genetic Algorithms for Inventory Lot-Sizing Problem with Supplier Selection under Storage Space
The objective of this research is to calculate the
optimal inventory lot-sizing for each supplier and minimize the total
inventory cost which includes joint purchase cost of the products,
transaction cost for the suppliers, and holding cost for remaining
inventory. Genetic algorithms (GAs) are applied to the multi-product
and multi-period inventory lot-sizing problems with supplier
selection under storage space. Also a maximum storage space for the
decision maker in each period is considered. The decision maker
needs to determine what products to order in what quantities with
which suppliers in which periods. It is assumed that demand of
multiple products is known over a planning horizon. The problem is
formulated as a mixed integer programming and is solved with the
GAs. The detailed computation results are presented.
[1] G.H. Goren, S. Tunali, and R. Jans, "A review of applications of genetic
algorithms in lot sizing", Journal of Intelligent Manufacturing. Springer
Netherlands. 2008.
[2] H. M. Wagner, and T. M. Whitin, "Dynamic version of the economic
lot-size model", Management Science. 5, pp, 89-96, 1958.
[3] C. Basnet and J. M. Y. Leung, "Inventory lot-sizing with supplier
selection", Computers and Operations Research. 32, pp, 1-14, 2005.
[4] J. H. Holland, Adaptation in Natural and Artificial Systems. The
University of Michigan Press, Ann Arbor. 1975.
[5] Z. Michalewicz, Genetic Algorithms + Data Structures = Evolution
Programs. AI Series. Springer-Verlag, New York. 1944.
[6] M. Gen, and R. Cheng, Genetic Algorithms and Engineering Design.
Wiley, New York. 1977.
[7] M. Gen, and R. Cheng, Genetic Algorithms and Engineering
Optimization. Wiley, New York. 2000.
[8] L. Davis, The handbook of genetic algorithms, Van Nostrand Reinhold,
New York. 1991.
[9] D. E. Goldberg, Genetic Algorithms in Search, Optimization and
Machine Learning. Addison-Wesley, Reading, MA. 1989.
[10] S. R. M. Mogador, A. Afsar, and B. Sohrabi, Inventory lot-sizing with
supplier selection using hybrid intelligent algorithm. Applied Soft
Computing. vol, 8, pp, 1523-1529, 2008.
[11] S. H. Chan, W. Chung, and S. Wadhwa, A hybrid genetic algorithm for
production and distribution. Omega. 33, pp, 345-355, 2005.
[12] R. Sarker, and C. Newton, A genetic algorithm for solving economic lot
size scheduling problem. Computers and Industrial Engineering. 42,
2002.
[13] K. Deb, Multi-Objective Optimization using Evolutionary Algorithms
Wiley, Chichester, 2001.
[14] J. Rezaei, and M. Davoodi, Genetic algorithm for inventory lot-sizing
with supplier selection under fuzzy demand and costs. Advances in
Applied Artificial Intelligence. Springer-Verlag Berlin Heidelberg.
4031, 2006.
[15] J. Rezaei, and M. Davoodi, A deterministic, multi-item inventory
model with supplier selection and imperfect quality. Applied
Mathematical Modelling. 32, pp, 2106-2116, 2008.
[1] G.H. Goren, S. Tunali, and R. Jans, "A review of applications of genetic
algorithms in lot sizing", Journal of Intelligent Manufacturing. Springer
Netherlands. 2008.
[2] H. M. Wagner, and T. M. Whitin, "Dynamic version of the economic
lot-size model", Management Science. 5, pp, 89-96, 1958.
[3] C. Basnet and J. M. Y. Leung, "Inventory lot-sizing with supplier
selection", Computers and Operations Research. 32, pp, 1-14, 2005.
[4] J. H. Holland, Adaptation in Natural and Artificial Systems. The
University of Michigan Press, Ann Arbor. 1975.
[5] Z. Michalewicz, Genetic Algorithms + Data Structures = Evolution
Programs. AI Series. Springer-Verlag, New York. 1944.
[6] M. Gen, and R. Cheng, Genetic Algorithms and Engineering Design.
Wiley, New York. 1977.
[7] M. Gen, and R. Cheng, Genetic Algorithms and Engineering
Optimization. Wiley, New York. 2000.
[8] L. Davis, The handbook of genetic algorithms, Van Nostrand Reinhold,
New York. 1991.
[9] D. E. Goldberg, Genetic Algorithms in Search, Optimization and
Machine Learning. Addison-Wesley, Reading, MA. 1989.
[10] S. R. M. Mogador, A. Afsar, and B. Sohrabi, Inventory lot-sizing with
supplier selection using hybrid intelligent algorithm. Applied Soft
Computing. vol, 8, pp, 1523-1529, 2008.
[11] S. H. Chan, W. Chung, and S. Wadhwa, A hybrid genetic algorithm for
production and distribution. Omega. 33, pp, 345-355, 2005.
[12] R. Sarker, and C. Newton, A genetic algorithm for solving economic lot
size scheduling problem. Computers and Industrial Engineering. 42,
2002.
[13] K. Deb, Multi-Objective Optimization using Evolutionary Algorithms
Wiley, Chichester, 2001.
[14] J. Rezaei, and M. Davoodi, Genetic algorithm for inventory lot-sizing
with supplier selection under fuzzy demand and costs. Advances in
Applied Artificial Intelligence. Springer-Verlag Berlin Heidelberg.
4031, 2006.
[15] J. Rezaei, and M. Davoodi, A deterministic, multi-item inventory
model with supplier selection and imperfect quality. Applied
Mathematical Modelling. 32, pp, 2106-2116, 2008.
@article{"International Journal of Mechanical, Industrial and Aerospace Sciences:56439", author = "Vichai Rungreunganaun and Chirawat Woarawichai", title = "Applying Genetic Algorithms for Inventory Lot-Sizing Problem with Supplier Selection under Storage Space", abstract = "The objective of this research is to calculate the
optimal inventory lot-sizing for each supplier and minimize the total
inventory cost which includes joint purchase cost of the products,
transaction cost for the suppliers, and holding cost for remaining
inventory. Genetic algorithms (GAs) are applied to the multi-product
and multi-period inventory lot-sizing problems with supplier
selection under storage space. Also a maximum storage space for the
decision maker in each period is considered. The decision maker
needs to determine what products to order in what quantities with
which suppliers in which periods. It is assumed that demand of
multiple products is known over a planning horizon. The problem is
formulated as a mixed integer programming and is solved with the
GAs. The detailed computation results are presented.", keywords = "Genetic Algorithms, Inventory lot-sizing, Supplier
selection, Storage space.", volume = "7", number = "2", pages = "258-6", }