An interactive particle swarm optimisation for selecting a product family and designing its supply chain

Authors:
S. R. Yadav;Yogesh Dashora;Ravi Shankar;Felix. T. S. Chan;M. K. Tiwari
Affiliations:
Department of Manufacturing Engineering, National Institute of Foundry and Forge Technology, 834003 Ranchi, India.;Department of Manufacturing Engineering, National Institute of Foundry and Forge Technology, 834003 Ranchi, India.;Department of Management Studies, Indian Institute of Technology, New Delhi, India.;Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pok Fu Lam Road, Hong Kong.;Department of Industrial Engineering and Management, Indian Institute of Technology, Kharagpur-721302, India
Venue:
International Journal of Computer Applications in Technology
Year:
2008

Citing 17
Cited 0

Market segmentation, cannibalization, and the timing of product introductions

Management Science
Principles on the benefits of manufacturing process flexibility

Management Science
Fuzzy set theory—and its applications (3rd ed.)

Fuzzy set theory—and its applications (3rd ed.)
Product family modeling for mass customization

ICC&IE Selected papers from the 22nd ICC&IE conference on Computers & industrial engineering
Holistic Customer Requirements and the Design-Select Decision

Management Science
Evolutionary Algorithms for Solving Multi-Objective Problems

Evolutionary Algorithms for Solving Multi-Objective Problems
Product Variety, Supply Chain Structure, and Firm Performance: Analysis of the U.S. Bicycle Industry

Management Science
Appropriateness and Impact of Platform-Based Product Development

Management Science
Product Differentiation and Commonality in Design: Balancing Revenue and Cost Drivers

Management Science
Process Flexibility in Supply Chains

Management Science
Approximating the Nondominated Front Using the Pareto Archived Evolution Strategy

Evolutionary Computation
MOPSO: a proposal for multiple objective particle swarm optimization

CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
An overview of evolutionary algorithms in multiobjective optimization

Evolutionary Computation
A cooperative multi colony ant optimization based approach to efficiently allocate customers to multiple distribution centers in a supply chain network

ICCSA'05 Proceedings of the 2005 international conference on Computational Science and Its Applications - Volume Part IV
Multiobjective evolutionary algorithms: a comparative case studyand the strength Pareto approach

IEEE Transactions on Evolutionary Computation
A fast and elitist multiobjective genetic algorithm: NSGA-II

IEEE Transactions on Evolutionary Computation
Handling multiple objectives with particle swarm optimization

IEEE Transactions on Evolutionary Computation

Quantified Score

Hi-index	0.00

Visualization

Abstract

A platform-based product development with mixed market-modular strategy can maintain product differentiation and help trade-off the cost and price premium drawing capability. This paper formulates a multi-objective problem to select a product family and design its supply chain and uses an Interactive Particle Swarm Optimisation (IPSO) approach. A case study for a wiring harness supplier of an Automated Guided Vehicle (AGV) manufacturer is considered and IPSO is implemented to solve it. The results establish that the platform-based product development serves the purpose of maintaining market diversity with near optimal cost and profits; more explorative insights are concern of future research.