Book Chapter10.1007/978-3-642-15621-2_5
Multi-objective particle swarm optimization control technology and its application in batch processes
Li Jia,Dashuai Cheng,Luming Cao,Zongjun Cai,Min-Sen Chiu +4 more
- 17 Sep 2010
- pp 36-44
TL;DR: An improved multi-objective particle swarm optimization based on pareto-optimal solutions is proposed, which shows that the quality at the end of each batch can approximate the desire value sufficiently and the input trajectory converges; thus verify the efficiency and practicability of the algorithm.
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Abstract: In this paper, considering the multi-objective problems in batch processes, an improved multi-objective particle swarm optimization based on pareto-optimal solutions is proposed. In this method, a novel diversity preservation strategy that combines the information on distance and angle into similarity judgment is employed to select global best and thus guarantees the convergence and the diversity characteristics of the pareto front. As a result, enough pareto solutions are distributed evenly in the pareto front. Lastly, the algorithm is applied to a classical batch process. The results show that the quality at the end of each batch can approximate the desire value sufficiently and the input trajectory converges; thus verify the efficiency and practicability of the algorithm.
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TL;DR: The Sigma method is introduced as a new method for finding best local guides for each particle of the population from a set of Pareto-optimal solutions and the results are compared with the results of a multi-objective evolutionary algorithm (MOEA).
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Konstantinos E. Parsopoulos,Michael N. Vrahatis +1 more
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TL;DR: Critical aspects of the VEGA approach for Multiobjective Optimization using Genetic Algorithms are adapted to the PSO framework in order to develop a multi-swarm PSO that can cope effectively with MO problems.
Multiobjective optimization using dynamic neighborhood particle swarm optimization
Xiaohui Hu,R.C. Eberhart +1 more
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TL;DR: This paper presents a particle swarm optimization algorithm modified by using a dynamic neighborhood strategy, new particle memory updating, and one-dimension optimization to deal with multiple objectives for multiobjective optimization problems.
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Stage-based process analysis and quality prediction for batch processes
Ningyun Lu,Furong Gao +1 more
TL;DR: In this paper, a process analysis and quality prediction scheme based on stage-based PLS modeling for batch processes is proposed, without any requirement of prior process knowledge, the scheme first divides a...
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