By Iftekhar A Karimi, Rajagopalan Srinivasan
Vol. 1. half A -- v. 2. half B
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Extra resources for 11th International Symposium on Process Systems Engineering
In this case, simulation must be used to evaluate EG y [ Lkjt|J kt ] , since this quantity no longer has a closed form. Under the mixed model of demand, customers’ unshaped product choices reflect on their personal values of α and β , giving insight into each customer’s sensitivity to shaping actions, and the likelihood of accepting specific substitutes. , Revelt and Train (1999)), or more generally, on their history of product choices, we obtain an individualized mixing distribution, G y| j , that is used to assess various targeted action hs , a shaping attribute ~ z ( hs ) and an alternative product set J ( hs ) .
Springer. 97-115. , P. Kouvelis, Z. Tian. 2009. Dynamic pricing and inventory control of substitute products. Manufacturing and Service Operations Management, 11(2), 317-339. , M. M. J. Peters. 2009. Managing Product Availability in an Assemble-To-Order Supply Chain with Multiple Customer Segments. OR Spectrum, 31, 257280. Ervolina, T. and B. Dietrich. 2001. Moving Toward Dynamic Available-to-Promise. In: Gass, S. and Jones. T. ) Supply Chain Management Practice and Research: Status and Future Directions.
Instead, we solve the MDP using approximate linear programming, which is a version of approximate dynamic programming (Powell 2008). Normal distributions are approximated by the GaussHermite quadrature. The shaping decisions are then chosen greedily with respect to the approximate value function. 16 Dietrich et al. 5. Numerical Experiments In this section, we evaluate the effectiveness of demand shaping, as it is depicted in Sections 3 and 4, in minimizing backlogging costs that result in the presence of unbalanced supply and demand.