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...

This paper presents a new multi objective heuristic algorithm for Dynamic Economic Load Dispatch (DELD) problem soultion with transmission losses based on new version of the Particle Swarm Optimization (PSO) algorithm, which called Multi Objective PSO (MOPSO) method. The proposed algorithm is based on multi objective meta-heuristics technique that evaluates a set of the Pareto solutions systema...

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 new hybrid multi-objective, multivariable optimizer utilizing Strength Pareto Evolutionary Algorithm (SPEA), Non-dominated Sorting Differential Evolution (NSDE), and Multi-Objective Particle Swarm (MOPSO) has been created and tested. The optimizer features automatic switching among these algorithms to expedite the convergence of the optimal Pareto front in the objective function(s) space. The...

This paper presents the application of modified form of Particle Swarm Optimization as an optimization technique to the reconfiguration of electric distribution systems. The intended reconfiguration is an optimization and decision-making process which considers the maximization of the number of loads supplied associated to the minimization of the number of closed switches. A novel selection reg...

A multi-objective particle swarm optimization (MOPSO) approach is presented for generating Pareto-optimal solutions for reservoir operation problems. This method is developed by integrating Pareto dominance principles into particle swarm optimization (PSO) algorithm. In addition, a variable size external repository and an efficient elitist-mutation (EM) operator are introduced. The proposed EM-...

AbstrAct: Muti-objective optimization deals with the simultaneous optimization of two or more conflicting objective functions in real-life systems. This paper deals with the multi-objective optimization in service systems. The goal of service systems is to provide cost-efficient service to customers, while at the same time, reducing the customer waiting time for service. In general, a low cost ...

The paper presents a novel Modulated Power Filter and Compensator (MPFC) scheme for voltage stability, energy conservation, loss reduction, power factor correction, and power quality enhancement for electric distribution systems based on Multi-Objective Particle Swarm Optimisation (MOPSO). The MPFC scheme was developed by the first author to vary the shunt power filter equivalent admittance, mo...

A novel multi-objective evolutionary algorithm (MOEA) is developed based on Imperialist Competitive Algorithm (ICA), a newly introduced evolutionary algorithm (EA). Fast non-dominated sorting and the Sigma method are employed for ranking the solutions. The algorithm is tested on six well-known test functions each of them incorporate a particular feature that may cause difficulty to MOEAs. The n...

This paper presents a new multi-objective optimization algorithm in which multi-swarm cooperative strategy is incorporated into particle swarm optimization algorithm, called multi-swarm cooperative multi-objective particle swarm optimizer (MC-MOPSO). This algorithm consists of multiple slave swarms and one master swarm. Each slave swarm is designed to optimize one objective function of the mult...