TY  - JOUR
T1  - Genetic Algorithm Approach to Joint Optimization for Product Line and Ordering Quantity
AU - , Daniel J. Fonseca AU - , Sidhartha Shishoo AU - , Keith Williams 
JO  - Research Journal of Applied Sciences
VL  - 2
IS  - 1
SP  - 43
EP  - 47
PY  - 2007
DA  - 2001/08/19
SN  - 1815-932x
DO  - rjasci.2007.43.47
UR  - https://makhillpublications.co/view-article.php?doi=rjasci.2007.43.47
KW  - Genetic algorithms
KW  -product line
KW  -quantity order
KW  -joint optimization
AB  - There is a growing consensus among product managers that determining the optimal length of product line is a crucial decision that affects the overall strategy and finance of a company.  Product line composition has clear financial implications that can hamper the profitability of an organization. Equally important is the ordering strategy that would determine the quantity of each product type and the timing of each order for replenishing the stocks of items in the product line.  This study describes a genetic algorithm model  that  simultaneously  optimizes the product line composition and the ordering quantity so to maximize total profits.
ER  -