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Research Journal of Applied Sciences

Genetic Algorithm Approach to Joint Optimization for Product Line and Ordering Quantity
Daniel J. Fonseca , Sidhartha Shishoo and Keith Williams

Abstract: 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.

How to cite this article
Daniel J. Fonseca , Sidhartha Shishoo and Keith Williams , 2007. Genetic Algorithm Approach to Joint Optimization for Product Line and Ordering Quantity. Research Journal of Applied Sciences, 2: 43-47.

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