10.6084/m9.figshare.11400639.v1 Evans Sowah Okpoti Evans Sowah Okpoti In-Jae Jeong In-Jae Jeong A decentralized coordination algorithm for multi-objective linear programming with block angular structure Taylor & Francis Group 2019 Collaborative optimization decentralized coordination multi-objective linear programming block angular structure multi-agent 2019-12-18 21:02:56 Journal contribution https://tandf.figshare.com/articles/journal_contribution/A_decentralized_coordination_algorithm_for_multi-objective_linear_programming_with_block_angular_structure/11400639 <p>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.</p>