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...

Full description

Bibliographic Details
Main Author: Jalora, Anshu
Other Authors: Peters, Brett A.
Format: Others
Language:en_US
Published: Texas A&M University 2006
Subjects:
Online Access:http://hdl.handle.net/1969.1/4421
id ndltd-tamu.edu-oai-repository.tamu.edu-1969.1-4421
record_format oai_dc
spelling ndltd-tamu.edu-oai-repository.tamu.edu-1969.1-44212013-01-08T10:38:30ZOrder acceptance and scheduling at a make-to-order system using revenue managementJalora, AnshuRevenue ManagementMake to OrderMake-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.Texas A&M UniversityPeters, Brett A.2006-10-30T23:33:16Z2006-10-30T23:33:16Z2006-082006-10-30T23:33:16ZBookThesisElectronic Dissertationtext453814 byteselectronicapplication/pdfborn digitalhttp://hdl.handle.net/1969.1/4421en_US
collection NDLTD
language en_US
format Others
sources NDLTD
topic Revenue Management
Make to Order
spellingShingle Revenue Management
Make to Order
Jalora, Anshu
Order acceptance and scheduling at a make-to-order system using revenue management
description 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.
author2 Peters, Brett A.
author_facet Peters, Brett A.
Jalora, Anshu
author Jalora, Anshu
author_sort Jalora, Anshu
title Order acceptance and scheduling at a make-to-order system using revenue management
title_short Order acceptance and scheduling at a make-to-order system using revenue management
title_full Order acceptance and scheduling at a make-to-order system using revenue management
title_fullStr Order acceptance and scheduling at a make-to-order system using revenue management
title_full_unstemmed Order acceptance and scheduling at a make-to-order system using revenue management
title_sort order acceptance and scheduling at a make-to-order system using revenue management
publisher Texas A&M University
publishDate 2006
url http://hdl.handle.net/1969.1/4421
work_keys_str_mv AT jaloraanshu orderacceptanceandschedulingatamaketoordersystemusingrevenuemanagement
_version_ 1716503503931703296