Notice of RetractionCrank block steering mechanism optimization for forklift truck based on PSO

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

Crank block steering mechanism optimization is a nonlinear constrained optimization problem, which is important for forklift truck to get preferable steering performance. Particle swarm optimization (PSO) with feasibility-based rules is a swarm intelligent algorithm proposed to solve constrained optimization problems simply and effectively. Therefore, it is used to optimize crank block steering mechanism of forklift truck, which will try to minimize the maximal error of outer wheel steering angle, maximize the minimal transmission angle and improve the force transmission. Experimental results obtained by PSO with feasibility-based rules are compared with those obtained by enumeration algorithm which is reliable for optimization problems. The comparison results showed that particle swarm optimization with feasibility-based rules can get same optimal results as enumeration algorithm in much less calculation times.