To resolving the conflict in engineering optimization design of highly complex and nonlinear constraints, a new particle swarm optimization algorithm with adaptive inertia weight is proposed. In this algorithm, inertia weight is adaptively changed according to the current evolution speed and aggregation degree of the swarm, which provides the algorithm with dynamic adaptability, enhances the se...

Particle swarm optimization (PSO) has shown to be a robust and efficient optimization algorithm therefore PSO has received increased attention in many research fields. This paper demonstrates the feasibility of applying the Dynamic Inertia Weight Particle Swarm Optimization to solve a Non-Polynomial (NP) Complete puzzle. This paper presents a new approach to solve the Nonograms Puzzle using Dyn...

Optimization of composite laminates requires the satisfaction constraints where design ply thicknesses and orientations can only take discrete values prescribed by manufacturers. Heuristics such as particle swarm or genetic algorithms are inefficient in cases because they provide suboptimal solutions when number variables is large. They also computationally expensive handling combinatorial natu...

This paper proposes a combined electromagnetic and mechanical topology optimization for weight reduction in electrical machines based on Finite Element Analysis (FEA) Evolutionary Structural Optimization (ESO). The devised method is an on-off-type algorithm with adaptative mesh which low flux density Von Mises stress cells are removed successively from first machine design. With this approach, ...