An Optimization Framework for Product Design

Authors:
Leyuan Shi;Sigurdur Ólafsson;Qun Chen
Affiliations:
-;-;-
Venue:
Management Science
Year:
2001

Citing 0
Cited 11

A combined procedure for optimization via simulation

ACM Transactions on Modeling and Computer Simulation (TOMACS)
Conjoint Optimization: An Exact Branch-and-Bound Algorithm for the Share-of-Choice Problem

Management Science
An improved nested partitions algorithm based on simulated annealing in complex decision problem optimization

WSEAS Transactions on Computers
Nested Partitioning for the Minimum Energy Broadcast Problem

Learning and Intelligent Optimization
Solving Beam-Angle Selection and Dose Optimization Simultaneously via High-Throughput Computing

INFORMS Journal on Computing
A Branch-and-Price Approach to the Share-of-Choice Product Line Design Problem

Management Science
An Improved Nested Partitions Algorithm Based on Simulated Annealing in Complex Decision Problem Optimization

ICIC '07 Proceedings of the 3rd International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence
PaRS: parallel and near-optimal grid-based cell sizing for library-based design

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
A new hybrid algorithm for feature selection and its application to customer recognition

COCOA'07 Proceedings of the 1st international conference on Combinatorial optimization and applications
Hybrid nested partitions algorithm for scheduling in job shop problem

ROBIO'09 Proceedings of the 2009 international conference on Robotics and biomimetics
Hybrid metaheuristics in combinatorial optimization: A survey

Applied Soft Computing

Quantified Score

Hi-index	0.01

Visualization

Abstract

An important problem in the product design and development process is to use the part-worths preferences of potential customers to design a new product such that market share is maximized. The authors present a new optimization framework for this problem, the nested partitions (NP) method. This method is globally convergent and may utilize existing heuristic methods to speed its convergence. We incorporate several known heuristics into this framework and demonstrate through numerical experiments that using the NP method results in superior product designs. Our numerical results suggest that the new framework is particularly useful for designing complex products with many attributes.