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method for the optimization of product development resource allocation

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Date Issued:
1997
Summary:
This thesis presents a model designed to optimize the allocation of corporate resources required for the success of a product in the marketplace. The product development resources used in the model are: market research, applied research, product design, cost reduction and advertising. The key goals of this thesis are to provide industry with a usable tool: (1) Implement strategic plans through effective budgeting; (2) Optimize both short and long term profits; (3) Evaluate the impact of resource inter-dependencies; (4) Enable accountability that leads to goal achievement and checks unnecessary growth; (5) Remove much of the negative political and emotional variability; (6) Easily adapt to internal and external changes; (7) Output a specific allocation for each resource as a percentage of sales; (8) Output an estimate of future profitability. Genetic Algorithms are particularly well suited for this application because an exact optima is not required and the search space can be extremely large, complex, and non-linear.
Title: A method for the optimization of product development resource allocation.
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Name(s): Worp, Nicholas Jacob.
Florida Atlantic University, Degree grantor
Han, Chingping (Jim), Thesis advisor
College of Engineering and Computer Science
Department of Ocean and Mechanical Engineering
Type of Resource: text
Genre: Electronic Thesis Or Dissertation
Issuance: monographic
Date Issued: 1997
Publisher: Florida Atlantic University
Place of Publication: Boca Raton, Fla.
Physical Form: application/pdf
Extent: 107 p.
Language(s): English
Summary: This thesis presents a model designed to optimize the allocation of corporate resources required for the success of a product in the marketplace. The product development resources used in the model are: market research, applied research, product design, cost reduction and advertising. The key goals of this thesis are to provide industry with a usable tool: (1) Implement strategic plans through effective budgeting; (2) Optimize both short and long term profits; (3) Evaluate the impact of resource inter-dependencies; (4) Enable accountability that leads to goal achievement and checks unnecessary growth; (5) Remove much of the negative political and emotional variability; (6) Easily adapt to internal and external changes; (7) Output a specific allocation for each resource as a percentage of sales; (8) Output an estimate of future profitability. Genetic Algorithms are particularly well suited for this application because an exact optima is not required and the search space can be extremely large, complex, and non-linear.
Identifier: 9780591625202 (isbn), 15519 (digitool), FADT15519 (IID), fau:12281 (fedora)
Collection: FAU Electronic Theses and Dissertations Collection
Note(s): College of Engineering and Computer Science
Thesis (M.S.)--Florida Atlantic University, 1997.
Subject(s): Genetic algorithms
Resource allocation
Strategic planning
Business planning
Held by: Florida Atlantic University Libraries
Persistent Link to This Record: http://purl.flvc.org/fcla/dt/15519
Sublocation: Digital Library
Use and Reproduction: Copyright © is held by the author, with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Use and Reproduction: http://rightsstatements.org/vocab/InC/1.0/
Host Institution: FAU
Is Part of Series: Florida Atlantic University Digital Library Collections.