The cross-entropy method in multi-objective optimisation: An assessment
MetadataShow full item record
Solving multi-objective problems requires the evaluation of two or more conflicting objective functions, which often demands a high amount of computational power. This demand increases rapidly when estimating values for objective functions of dynamic, stochastic problems, since a number of observations are needed for each evaluation set, of which there could be many. Computer simulation applications of real-world optimisations often suffer due to this phenomenon. Evolutionary algorithms are often applied to multi-objective problems. In this article, the cross-entropy method is proposed as an alternative, since it has been proven to converge quickly in the case of single-objective optimisation problems. We adapted the basic cross-entropy method for multi-objective optimisation and applied the proposed algorithm to known test problems. This was followed by an application to a dynamic, stochastic problem where a computer simulation model provides the objective function set. The results show that acceptable results can be obtained while doing relatively few evaluations.
Showing items related by title, author, creator and subject.
Mathematical optimisation of location and design of windows by considering energy performance, lighting and privacy of buildingsHammad, A.; Akbarnezhad, A.; Grzybowska, H.; Wu, Peng; Wang, X. (2018)© 2018, Ahmed Hammad, Ali Akbarnezhad, Hanna Grzybowska, Peng Wu and Xiangyu Wang. Purpose: The Middle East and North Africa (MENA) region is known for its extreme weather conditions during Summer. A major determinant of ...
Long, Q.; Wu, Changzhi; Huang, T.; Wang, Xiangyu (2015)In this paper, we propose a genetic algorithm for unconstrained multi-objective optimization. Multi-objective genetic algorithm (MOGA) is a direct method for multi-objective optimization problems. Compared to the traditional ...
Yao, Hong Mei; Tade, Moses; Mohammed, Feisal Ali (2012)Process optimisation has been at the core of design and retrofit of process industries. Traditional process design focuses on plant operations to minimise costs or maximise profits using performance indicators of conversion, ...