作者: Hrishikesh Dewan , Raksha B. Nayak , V. Susheela Devi
DOI: 10.1007/978-3-319-03844-5_46
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摘要: Multi-objective optimization problem is an important part in solving a wide number of engineering and scientific applications. To-date, most the research has been conducted static multi-objective problems where decision variables and/or objective functions do not change over period time. In dynamic environment, particles non dominated solution set during specific iteration may no longer be valid due to underlying system. As result, traditional techniques for cannot applied functions. Further, with increase variables/objective functions, single system based optimizer will take long time compute non-dominated set. this paper, we present peer-to-peer distributed particle swarm algorithm that tracks able produce diversified dense non- using network Our algorithms are tested known benchmark results reported. To our knowledge, first its kind areas optimization.