Real world problems often present multiple, frequently conflicting, objectives. The research for optimal solutions of multi-objective problems can be achieved through means of genetic algorithms, which are inspired by the natural process of evolution: an initial population of solutions is randomly generated, then pairs of solutions are selected and combined in order to create new solutions slig...

In order to improve the structural stiffness of gravure cell structure in solid printing process and realize a lightweight design, multi-objective optimization design method was proposed optimize parameters direct laser engraving structure. this paper, based on characteristics analysis contact force, ANSYS parametric language (APDL) used conduct finite element microstructure regular hexagonal c...

This This paper describes the use of a Genetic Algorithm (GA) for the problem of point-to-point robot path planning and control. The problem consist of generating trajectories, for a two d.o.f robot to move from a starting position to a destination in a task space, represented by a two dimensional map, with obstacles that the Robot must evade. The role of the GA is to optimize possible paths ba...

Aerodynamic performances of ground vehicle continuously improve and a lot both wind tunnel measurements Computational Fluid Dynamics (CFD) investigations contribute in the identification local zones where shape deformation can lead to drag force reduction. Gradient-based optimization with optimal system involving CFD models is one powerful methods for optimization, but genetic algorithm applied...

The paper presents a family of novel switched smart filter compensated devices using Green Plug Smart Filter Soft Starter GP-SF-SS devices for small single phase induction motors used in air-conditioning, ventilation and water pumping. GP-SFSS devices are equipped with a dynamic online error driven optimally tuned modified PID controller that ensures improved power factor, reduced feeder losses...

This paper proposes a framework for time-efficiently finding multiple answers that meet logical constraints and are Pareto-optimal objective functions. The proposed determines set of optimal by iteratively replacing definite clauses. Clause replacement is performed using SAT solver consisting equivalent transformation rules (ETRs). An ETR replaces clause with one or more clauses while preservin...

Elitism and sharing are two mechanisms that are believed to improve the performance of a multiobjective evolutionary algorithm (MOEA). Using a new empirical inquiry framework, this paper studies the effect of elitism and sharing design choices using a benchmark suite of two-criterion problems. Performance is assessed, via known metrics, in terms of both closeness to the true Pareto-optimal fron...

In this paper, we investigate the issue of convergence in multiobjective optimization problems when using a MultiObjective Genetic Algorithm (MOGA) to determine the set of Pareto optimal solutions. Additionally, given a Pareto set for a multi-objective problem, the mapping between the performance and design space is studied to determine design variable configurations for a given set of performa...

The role of phases and their interplay in molecular vibrational quantum computing with multiple qubits Chirp-driven vibrational distribution in transition metal carbonyl complexes Phys. Robustness of quantum gates operating on the high frequency modes of MnBr(CO) 5 Comment on " Anharmonic properties of the vibrational quantum computer " [J. Monotonic convergent optimal control theory with stric...