The primary function of a suspension system of a vehicle is to isolate the road excitations experienced by the tires from being transmitted to the passengers. In this paper, we formulate an optimal vehicle suspension design problem with the quarter-car vehicle dynamic model. A new multi-objective genetic algorithm is used for Pareto optimization of a two-degree of freedom vehicle vibration mode...

0017-9310/$ see front matter 2009 Elsevier Ltd. A doi:10.1016/j.ijheatmasstransfer.2009.03.069 * Corresponding author. Tel.: +1 518 276 2843; fax E-mail address: [email protected] (M.K. Jensen). A multi-objective thermal design optimization and comparative study of electronics cooling technologies is presented. The cooling technologies considered are: continuous parallel micro-channel heat sinks, ...

An evolutionary multi-objective optimization tool based on an estimation of distribution algorithm is proposed. The algorithm uses the ranking method of non-dominated sorting genetic algorithm-II and the Parzen estimator to approximate the probability density of solutions lying on the Pareto front. The proposed algorithm has been applied to different types of test case problems and results show...

Evolutionary Algorithms have been applied to single and multiple objectives optimization problems, with a strong emphasis on problems, solved through numerical simulations. However in several engineering problems, there is limited availability of suitable models and there is need for optimization of realistic or experimental configurations. The multiobjective optimization of an experimental set...

1 Abstract Multi-objective optimization addresses problems with several design objectives, which are often conflicting, placing different demands on the design variables. In contradiction to traditional optimization methods, which combine all objectives into a single figure of merit, parallel optimization strategies such as evolutionary algorithms allow direct convergence to the Pareto front. T...

This paper presents an approach to incorporate Pareto dominance into the differential evolution (DE) algorithm in order to solve optimization problems with more than one objective by using the DE algorithm. Unlike the existing proposals to extend the DE to solve multiobjective optimization problems, our algorithm uses an external archive to store nondominated solutions. In order to generate tri...

We develop a novel coevolutionary algorithm based upon the concept of Pareto optimality. The Pareto criterion is core to conventional multi-objective optimization (MOO) algorithms. We can think of agents in a coevolutionary system as performing MOO, as well: An agent interacts with many other agents, each of which can be regarded as an objective for optimization. We adapt the Pareto concept to ...

This study proposes a bi-objective model for capacitated multi-vehicle allocation of customers to potential distribution centers (DCs).The optimization objectives are to minimize transit time and total cost including opening cost, assumed for opening potential DCs and shipping cost from DCs to the customers where considering heterogeneous vehicles lead to a more realistic model and cause more c...