The Application of Memetic Algorithms for Forearm Crutch Design: A Case Study

Document Type

Article

Publication Date

3-11-2011

Abstract

Product design has normally been performed by teams, each with expertise in a specific discipline such as material, structural, and electrical systems. Traditionally, each team would use its member's experience and knowledge to develop the design sequentially. Collaborative design decisions explore the use of optimization methods to solve the design problem incorporating a number of disciplines simultaneously. It is known that such optimized product design is superior to the design found by optimizing each discipline sequentially due to the fact that it enables the exploitation of the interactions between the disciplines. In this paper, a bi-level decentralized framework based on Memetic Algorithm (MA) is proposed for collaborative design decision making using forearm crutch as the case. Two major decisions are considered: the weight and the strength. We introduce two design agents for each of the decisions. At the system level, one additional agent termed facilitator agent is created. Its main function is to locate the optimal solution for the system objective function which is derived from the Pareto concept. Thus to Pareto optimum for both weight and strength is obtained. It is demonstrated that the proposed model can converge to Pareto solutions.

Comments

Copyright © 2011 Teresa Wu et al.

This is an open access article published by Hindawi and distributed under the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

The "Link to Full Text" opens the full open access article at the publisher website. A PDF version of the published article is available on that page.

DOI

10.1155/2011/162580

Source Publication

Mathematical Problems in Engineering

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