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A decentralized coordination algorithm for multi-objective linear programming with block angular structure

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journal contribution
posted on 18.12.2019 by Evans Sowah Okpoti, In-Jae Jeong

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.


This work was supported by the Basic Science Research Program through the National Research Foundation of Korea, funded by the Ministry of Education [grant number 2014R1A1A2058147] and the Ministry of Science, ICT and Future Planning (grant number 2017R1E1A1A03070435).