Article ID: | iaor2012268 |
Volume: | 13 |
Issue: | 1 |
Start Page Number: | 121 |
End Page Number: | 150 |
Publication Date: | Mar 2012 |
Journal: | Optimization and Engineering |
Authors: | Yacout Soumaya, Baril Chantal, Clment Bernard |
Keywords: | decision theory: multiple criteria, knowledge management, design |
To remain competitive and gain new shares of the market, industries must develop their products quickly while meeting the multiple customer requirements. To reduce product development time, the design step is often accomplished by several working groups working in parallel. These working groups are often decentralized and are supervised by a director. This paper focuses on solving a multi‐objective problem in a setting that is called a ‘decentralized environment.’ Collaborative optimization is a strategy used for solving problems in a decentralized environment. This strategy divides a problem into subproblems in order to give more autonomy to working groups, thus facilitating work in parallel. In this paper, collaborative optimization is paired with an interactive algorithm to solve multi‐objective problems in a decentralized environment. It can be easily adjusted within the structure of a development process in a given industry and allows collaboration between the director and his/her working groups. The algorithm captures the director’s and the working groups’ preferences and generates several Pareto‐optimal solutions. The algorithm was tested on a two‐bar structure problem. The results obtained match those published in the literature.