Constrained particle swarm optimisation for sequential quadratic programming
by Zach D. Richards
International Journal of Modelling, Identification and Control (IJMIC), Vol. 8, No. 4, 2009

Abstract: Sequential quadratic programming (SQP) methods are commonly used to solve constrained non-linear optimisation problems. However, in recent years there has been great improvement in using evolutionary algorithms to solve non-linear optimisations problems. The difficulty has been determining a correct method for implementing evolutionary algorithm for a non-linear optimisation problem with constraints. In this paper, we are combining the strengths of the traditional SQP method with an evolutionary algorithm, particle swarm optimisation (PSO) for solving a constrained non-linear optimisation problem with equality and inequality constraints. We propose a constrained PSO algorithm be used to solve the quadratic programming (QP) subproblem within the SQP method.

Online publication date: Wed, 09-Dec-2009

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