The paper deals with a topology optimization formulation that uses mixed-finite elements. The discretization scheme adopts not only displacements (as usual) but also stresses as primary variables. Two dual variational formulations based on the HellingerReissner variational principle are presented in continuous and discrete form. The use of this technique and the choice of nodal densities as opt...

The paper addresses key problems pertaining to the commonly used evolutionary approach to the search for optimal catalysts in chemical engineering. These are on the one hand the insufficient dealing in existing implementations of genetic algorithms with mixed optimization, which plays a crucial role in catalysis, on the other hand the narrow scope of genetic algorithms developed specifically fo...

This article discusses solving non-linear programming problems containing integer, discrete and continuous variables. The Part 1 of the article describes a novel optimization method based on Differential Evolution algorithm. The required handling techniques for integer, discrete and continuous variables are described including the techniques needed to handle boundary constraints as well as thos...

Metaheuristics is basically a higher level procedure, which generates a simpler procedure to solve an optimization problem. Optimization is the process of adjusting the inputs to or characteristics of a device, mathematical process, or experiment to find the minimum or maximum output or result. The input consists of variables; the process or function is known as the cost function, objective fun...

This paper proposes a novel population-based evolution algorithm named grouping-shuffling particle swarm optimization (GSPSO) by hybridizing particle swarm optimization (PSO) and shuffled frog leaping algorithm (SFLA) for continuous optimization problems. In the proposed algorithm, each particle automatically and periodically executes grouping and shuffling operations in its flight learning evo...

The shuffled frog leaping algorithm (SFLA) easily falls into local optimum when it solves multioptimum function optimization problem, which impacts the accuracy and convergence speed. Therefore this paper presents grouped SFLA for solving continuous optimization problems combined with the excellent characteristics of cloud model transformation between qualitative and quantitative research. The ...

Programmable Logic Controller (PLC) has been widely used in the industrial control. Inherently, the PLCbased system is a class of Hybrid Dynamical System (HDS) in which continuous state of the plant is controlled by the discrete logic-based controller. This paper firstly presents the formal algebraic model of the PLC-based control systems which enable the designer to formulate the various kinds...

The ultimate goal of designing a symmetric-key cryptographic primitive often can be formulated as an optimization problem. So far, these problems mainly have been solved with trivial algorithms such as brute force or random search. We show that a more advanced and equally versatile class of search algorithms, called metaheuristics, can help to tackle optimization problems related to design of s...

Procedures like start-up, product change-over, or shutdown of processing systems usually involve the manipulation of continuous and discrete controls. To optimize such procedures, the use of hybrid models is often appropriate to account for the change of dynamics during the transition. Some recently developed approaches for hybrid system optimization are based on mixed-integer linear programmin...