In the present study, an efficient optimization algorithm is proposed to optimal design of structures. The proposed algorithm is an improved particle swarm optimization (PSO) which its global search performance is enhanced by employing the concept of cellular automata (CA). In the so-called improved particle swarm optimization (IPSO) algorithm a new cellular automata based term is added to the ...

in recent years, reducing emissions has become an important issue. besides reducing the economic costs, reducing the fuel consumption decreases emissions, pollutant impact and increases society health as well. green vehicle routing problem are a major key to reduce hazardous effects of transportation such as air pollution, greenhouse gas (ghg) emissions, noise and the like. generally, the amoun...

in this paper, an integration of improve particle swarm optimization (ipso) incombination with successive quadratic programming (sqp) so called ipso-sqpalgorithm is proposed to solve time optimal bang-bang control problems. theprocedure is found not sensitive to the initial guess of the solution. due to randomselection in the first stage of the search process, the chance of converging to theglo...

This paper presents an improved particle swarm optimization (IPSO) to solve constrained optimization problems, which handles constraints based on certain feasibility-based rules. A turbulence operator is incorporated into IPSO algorithm to overcome the premature convergence. At the same time, a set called FPS is proposed to save those locating in the feasible region. Different from the standard...

This paper presents an optimal design of linear phase digital high pass finite impulse response (FIR) filter using Improved Particle Swarm Optimization (IPSO). In the design process, the filter length, pass band and stop band frequencies, feasible pass band and stop band ripple sizes are specified. FIR filter design is a multi-modal optimization problem. An iterative method is introduced to fin...

An improved particle swarm optimizer (IPSO) with artificial immune algorithm (AIA) is proposed based on basic particle swarm optimization (BPSO). IPSO which is divided into two phases during the evolutionary process is different from BPSO. AIA remaining the diversity of population is applied in the first phase. Sub-population is formed by the optimum values sorted near the top from the first ph...

In this paper, an intelligent-gradient based algorithm is proposed to solve time optimal bang-bang control problem. The proposed algorithm is a combination of an intelligent algorithm called improved particle swarm optimization algorithm (IPSO) in the first stage of optimization process together with a gradient-based algorithm called successive quadratic programming method (SQP) in the second s...

The paper puts forward an unmanned aerial vehicle (UAV) fixed-point reconnaissance route planning method. The method introduces the improved particle swarm optimization (IPSO) method to the planning of UAV reconnaissance route and adds the objective value, effective reconnaissance route and other factors affecting UAV reconnaissance route in the objective function of particle swam to obtain the...