A decentralized coordination algorithm for multi-objective linear programming with block angular structure. Issue 2 (1st February 2021)

• Record Type: Journal Article
• Authors: Sowah Okpoti, Evans; Jeong, In-Jae
• Is Part Of: Engineering optimization. Volume 53:Issue 2(2021)
• Page Start: 185
• Page End: 205
• Publication Date: 2021-02-01
• Subjects: Collaborative optimization -- decentralized coordination -- multi-objective linear programming -- block angular structure -- multi-agent; Engineering design -- Periodicals; Mathematical optimization -- Periodicals; 620.0042
• DOI: 10.1080/0305215X.2019.1698035
• Languages: English
• ISSNs: 0305-215X

Abstract

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.