in this article, multiple-product pvrp with pickup and delivery that is used widely in goods distribution or other service companies, especially by railways, was introduced. a mathematical formulation was provided for this problem. each product had a set of vehicles which could carry the product and pickup and delivery could simultaneously occur. to solve the problem, two meta-heuristic methods...

Abstract The integration of Internet Things devices onto the Blockchain implies an increase in transactions that occur on Blockchain, thus increasing storage requirements. A solution approach is to leverage cloud resources for storing blocks within chain. paper, therefore, proposes two solutions this problem. first being improved hybrid architecture design which uses containerization create a s...

In present study, a three-step multi-objective optimization algorithm of cyclone separators is catered for the design objectives. First, the pressure drop (Dp) and collection efficiency (h) in a set of cyclone separators are numerically evaluated. Secondly, two meta models based on the evolved Group Method of Data Handling (GMDH) type neural networks are regarded to model the Dp and h as the re...

In this research, an intelligent multi-objective nonlinear model predictive control (NMPC) scheme is proposed for its application in the ‘on-line’ optimization of dynamical gas turbine model. The scheme proposed belongs to the sub-optimal NMPC strategies where near-optimal, instead of global optimal, control solutions are obtained at each control sampling time. The complexity of NMPC implementa...

Applying multi-objective particle swarm optimization (MOPSO) algorithm to multi-objective design of multimachine power system stabilizers (PSSs) is presented in this paper. The proposed approach is based on MOPSO algorithm to search for optimal parameter settings of PSS for a wide range of operating conditions. Moreover, a fuzzy set theory is developed to extract the best compromise solution. T...

A major difficulty in the use of metaheuristics (i.e. evolutionary and particle swarm algorithms) to deal with multi-objective optimization problems is the choice of a convenient point at which to stop computation. Indeed, it is difficult to find the best compromise between the stopping criterion and the algorithm performance. This paper addresses this issue using the Non-dominated Sorting Gene...

Pareto Based Multi Objective Optimization Algorithms, including Multi-Objective Particle Swarm Optimization (MOPSO), face several problems when applied to Multi Objective Optimization Problems with a large number of objective functions, especially the deterioration of the search ability. In the literature some techniques were proposed to overcome these limitations, among them the modification o...

This paper presents a new approach to treat reactive power (VAr) planning problem using multi-objective evolutionary algorithms. Specifically, Strength Pareto Evolutionary Algorithm (SPEA) and Multi-Objective Particle Swarm Optimization (MOPSO) approaches have been developed and successfully applied. The overall problem is formulated as a nonlinear constrained multi-objective optimization probl...

In the present study, multi-objective optimization of centrifugal pumps is performed at three steps. At the first step, η and NPSHr in a set of centrifugal pump are numerically investigated using commercial software. Two meta-models based on the evolved group method of data handling (GMDH) type neural networks are obtained, at the second step, for modeling of η and NPSHr with respect to geometr...

Flexible skin and continuous deformable control surface are the basic of adaptive wing technology for future aircraft. This paper presents a morphing trailing-edge its allocation method flying Unmanned Aerial Vehicle (UAV). Firstly, we apply Kriging to establish aerodynamic model trailing-edge, with initial sample points generated by non-uniform optimal Latin Hypercube Sampling (LHS). Then, bas...