Interactive multi-objective optimization using mobile application; application to multi-objective linear assiqnment problem
- Authors
- Kim, Shinmyeong; Jeong, In Jae
- Issue Date
- Jan-2019
- Publisher
- Association for Computing Machinery
- Keywords
- Empirical study; Interactive decentralized coordination; Multi-agent system; Multi-objective linear assignment programming
- Citation
- ACM International Conference Proceeding Series, pp.12 - 19
- Indexed
- SCOPUS
- Journal Title
- ACM International Conference Proceeding Series
- Start Page
- 12
- End Page
- 19
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/148476
- DOI
- 10.1145/3314527.3314538
- ISSN
- 0000-0000
- Abstract
- In the past decades, there has been a plenty of researches on multi-objective programming (MOP) problems due to the unreality of single-objective programming problems. However, multi-objective programming problems have also been discussed in terms of information security issues, the preference of people involved in decision-making and so on. A recently developed a decentralized coordination algorithm has the advantage of generating a single Pareto optimal solution under the condition that information of each agent involved in decision making is not shared. Nevertheless, this algorithm does not reflect the preference of each decision maker, and thus can generate a biased Pareto optimal solution. Therefore, in this study, we developed a mobile application that iteratively searches the Pareto optimal solution through an interactive decentralized coordination algorithm (IDCA) by interactively exchanging agent's preference information in the realm of multi-objective linear assignment problem. An empirical study was conducted to identify factors affecting to the generation of unbiased pareto solutions with 32 human decision makers.
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