A decentralized coordination algorithm for multi-objective linear programming with block angular structure
- Authors
- Okpoti, Evans Sowah; Jeong, In Jae
- Issue Date
- Feb-2021
- Publisher
- TAYLOR & FRANCIS LTD
- Keywords
- Collaborative optimization; decentralized coordination; multi-objective linear programming; block angular structure; multi-agent
- Citation
- ENGINEERING OPTIMIZATION, v.53, no.2, pp.185 - 205
- Indexed
- SCIE
SCOPUS
- Journal Title
- ENGINEERING OPTIMIZATION
- Volume
- 53
- Number
- 2
- Start Page
- 185
- End Page
- 205
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/142367
- DOI
- 10.1080/0305215X.2019.1698035
- ISSN
- 0305-215X
- Abstract
- This article considers linear multi-objective programming problems with block angular structure, which are analogous to multi-disciplinary optimization environments where disciplines must collaborate to achieve a common overall goal. In this decentralized environment, a mechanism to guide locally optimized decision makers' solutions to a Pareto-optimal solution without sharing the entire local information is developed. The mechanism is based on an augmented Lagrangian approach to generate a solution and is separated into two phases: phase I determines an ideal point for each of the single objectives and phase II searches for a compromise solution starting from a single ideal point. Theoretical results show that the algorithm converges and the solution generated is Pareto optimal. The algorithm's effectiveness is demonstrated via an illustrative example and a real-world bi-objective re-entrant flow-shop production planning problem. The real-world experimental results showed that the decentralized method had an average 50% better performance compared to other centralized methods.
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