Show simple item record
dc.description.abstract© Copyright 2016 Taylor & Francis Group, LLC. Multipoint approximation method (MAM) focuses on the development of metamodels for the objective and constraint functions in solving a mid-range optimization problem within a trust region. To develop an optimization technique applicable to mixed integer-continuous design optimization problems in which the objective and constraint functions are computationally expensive and could be impossible to evaluate at some combinations of design variables, a simple and efficient algorithm, coordinate search, is implemented in the MAM. This discrete optimization capability is examined by the well established benchmark problem and its effectiveness is also evaluated as the discreteness interval for discrete design variables is increased from 0.2 to 1. Furthermore, an application to the optimization of a lattice composite fuselage structure where one of design variables (number of helical ribs) is integer is also presented to demonstrate the efficiency of this capability.en_US
dc.format.extent22 - 35en_US
dc.relation.ispartofInternational Journal of Computational Methods in Engineering Science and Mechanicsen_US
dc.titleImplementation of Discrete Capability into the Enhanced Multipoint Approximation Method for Solving Mixed Integer-Continuous Optimization Problemsen_US
dc.rights.holder© 2016 Taylor & Francis
pubs.notesNot knownen_US

Files in this item


This item appears in the following Collection(s)

Show simple item record