Journal
APPLICATIONS OF EVOLUTIONARY COMPUTATION (EVOAPPLICATIONS 2017), PT II
Volume 10200, Issue -, Pages 99-109Publisher
SPRINGER INTERNATIONAL PUBLISHING AG
DOI: 10.1007/978-3-319-55792-2_7
Keywords
Robust optimization over time; Robust optimization; Dynamic optimization; Benchmark problems; Tracking moving optima; Particle swarm optimization; Multi-swarm algorithm
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Funding
- Faculty of Engineering and Technology, Liverpool John Moores University
- T-TRIG project by the UK Department for Transport
- Newton Institutional Links project by the UK BEIS via the British Council
- Newton Research Collaboration Programme by the UK BEIS via the Royal Academy of Engineering [3]
- Chartered Institute of Logistics and Transport
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Dynamic optimization problems (DOPs) are optimization problems that change over time, and most investigations in this area focus on tracking the moving optimum efficiently. However, continuously tracking a moving optimum is not practical in many real-world problems because changing solutions frequently is not possible or very costly. Recently, another practical way to tackle DOPs has been suggested: robust optimization over time (ROOT). In ROOT, the main goal is to find solutions that can remain acceptable over an extended period of time. In this paper, a new multi-swarm PSO algorithm is proposed in which different swarms track peaks and gather information about their behavior. This information is then used to make decisions about the next robust solution. The main goal of the proposed algorithm is to maximize the average number of environments during which the selected solutions' quality remains acceptable. The experimental results show that our proposed algorithm can perform significantly better than existing work in this aspect.
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