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Order acceptance and scheduling at a make-to-order system using revenue management

Make-to-order (MTO) systems have been traditionally popular in manufacturing
industries that either seek to provide greater variety to their customers or make
products that are unique to their customers. More recently, with shrinking product
life cycles, there is an increasing interest in operating as MTO systems. With the
tremendous success of revenue management techniques in the service industries over
the last three decades, there is a growing interest in applying these techniques in
MTO manufacturing industries.
In the present work, we consider three problems that apply revenue management
(RM) to on-date delivery MTO systems. In the first problem, we assume that all
orders completed in advance of their due-dates are stored at third party warehouses
and apply RM in computing efficient order acceptance and scheduling policies. We
develop an optimal solution scheme, and based on the insights gained on the structural
properties of the optimal solution, we develop a stochastic approximation scheme for
finding efficient solutions. Through computational studies on simulated problems, we
illustrate the potential of RM in improving net profits over popular practices.
In our second problem, we extend the RM model to consider presence of a certain
amount of first party warehousing capacity for storing the orders completed in advance
of their due-dates. We study the conditions under which it is desirable to consider the
holding cost aspects in the RM model. In our third problem, we develop a scheme for determining an efficient capacity of the first party warehouse that is used for
storing the orders completed in advance of their due-dates at an on-date delivery
MTO system. This scheme captures the completed orders storage demand resulting
from a RM based order acceptance and scheduling policy. We illustrate that when
booking horizon is large, considerable amount of savings in the holding costs can be
made with an efficiently sized first party warehouse.

Identiferoai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/4421
Date30 October 2006
CreatorsJalora, Anshu
ContributorsPeters, Brett A.
PublisherTexas A&M University
Source SetsTexas A and M University
Languageen_US
Detected LanguageEnglish
TypeBook, Thesis, Electronic Dissertation, text
Format453814 bytes, electronic, application/pdf, born digital

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