The work provides an exhaustive comparison of some representative families topology optimization methods for 3D structural optimization, such as the Solid Isotropic Material with Penalization (SIMP), Level-set, Bidirectional Evolutionary Structural Optimization (BESO), and Variational Topology (VARTOP) methods. main differences similarities these approaches are then highlighted from algorithmic...

This paper describes the adaptation of evolutionary algorithms (EAs) to the structural optimization of chemical engineering plants, using rigorous process simulation combined with realistic costing procedures to calculate target function values. To represent chemical engineering plants, a network representation with typed vertices and variable structure will be introduced. For this representati...

Many studies have attempted to specify alternative model configurations as fitting empirical data with the aid of structural equation modeling (SEM) method. However, significant path searching between constructs has increased in difficulty and complexity. One way to enhance modeling efficiency is evolutionary optimization by genetic algorithm (GA). This study applies the project management (PM)...

A smooth bidirectional evolutionary structural optimization (SBESO), as a version of SESO is proposed to solve the topological vibrating continuum structures for natural frequencies and dynamic compliance under transient load. weighted function introduced regulate mass stiffness matrix an element, which has inefficient element gradually removed from design domain if it were undergoing damage. A...

the markowitz’s optimization problem is considered as a standard quadratic programming problem that has exact mathematical solutions. considering real world limits and conditions, the portfolio optimization problem is a mixed quadratic and integer programming problem for which efficient algorithms do not exist. therefore, the use of meta-heuristic methods such as neural networks and evolutionar...

In this paper, we describe a new algorithm that consists in combining an eye-tracker for minimizing the fatigue of a user during the evaluation process of Interactive Evolutionary Computation. The approach is then applied to the Interactive OneMax optimization problem.

Pareto dominance-based multiobjective optimization has been successfully applied to constrained evolutionary during the last two decades. However, as another famous framework, decomposition-based not received sufficient attention from optimization. In this paper, we make use of solve problems (COPs). our method, first all, a COP is transformed into biobjective problem (BOP). Afterward, BOP deco...

Graph clustering is the detection of tightly connected regions in a graph. A clustering may yield structural information about the graph that is especially valuable in this data driven age. As graph clustering is considered to be an NP-hard optimization problem, the effort of accurately computing the best solution clustering for larger graphs is intractable. On these grounds, heuristics that se...