Hossein Ghiasi

Bio: Hossein Ghiasi is an academic researcher from McGill University. The author has contributed to research in topics: Multi-objective optimization & Composite laminates. The author has an hindex of 10, co-authored 14 publications receiving 772 citations.

A non-dominated sorting hybrid algorithm for multi-objective optimization of engineering problems

Abstract: Among numerous multi-objective optimization algorithms, the Elitist non-dominated sorting genetic algorithm (NSGA-II) is one of the most popular methods due to its simplicity, effectiveness and minimum involvement of the user. This article develops a multi-objective variation of the Nelder-Mead simplex method and combines it with NSGA-II in order to improve the quality and spread of the solutions. The proposed hybrid algorithm, called non-dominated sorting hybrid algorithm (NSHA), is compared with NSGA-II on several constrained and unconstrained test problems. The higher convergence rate and the wider spread of solutions obtained with NSHA make this algorithm a good candidate for engineering problems that require time-consuming simulation and analysis. To demonstrate this fact, NSHA is applied to the design of a carbon fibre bicycle stem simultaneously optimized for strength, weight and processing time.

Constrained Globalized Nelder—Mead Method for Simultaneous Structural and Manufacturing Optimization of a Composite Bracket:

Abstract: The optimized design of composite structures is a difficult task. It requires optimizing simultaneously both structural and manufacturing objectives. The objectives do not have closed form solutions and have multiple local optima that calls for a global search. This paper improves the global search method called GBNM (1), which is based on several restarts of the Nelder-Mead method. Two issues are addressed here. First, the restart procedure is improved by using a one-dimensional probability function and a weighted selection procedure. Second, nonlinear constraints are included by projecting the infeasible points onto the nonlinear constraints. The improved procedure is applied to four mathematical test functions. Numerical results show the proposed approach is more efficient in terms of computational time and probability of finding the global minimum. The improved GBNM is then applied to the simultaneous structural and manufacturing design of a Z-shaped composite bracket. The results are compared to those obtained with the genetic algorithm.

Buckling analysis and optimisation of variable angle tow composite plates

Abstract: Variable angle tow (VAT) placed composite laminates, where the fibre orientations continuously varying over the plane of each ply, generally exhibit variable stiffness properties. The stiffness tailoring of VAT plates through the design of fibre orientation distributions can substantially improve the buckling resistance, which is mainly due to the benign, non-uniform, in-plane load redistribution. In this work, a new mathematical definition is proposed to represent the general variation of fibre-orientation in the VAT plate. In this definition, the coefficients of polynomials are directly equal to the designed fibre angles at pre-selected control points. A Rayleigh–Ritz approach is used to determine the prebuckling loads distributions and critical buckling load of VAT plates. It provides a more efficient means to evaluate the buckling load of VAT laminates, compared with other numerical solutions. Subsequently, preliminary optimisation of VAT plates for maximum buckling load is done using the proposed definition of non-linear variation of fibre angles. Results obtained for simply supported square VAT plates are compared with optimal results reported in the literature. Finally, long VAT plates with one free edge and others simply supported are studied to demonstrate the viability of the proposed modelling strategy.