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The objective of portfolio optimization is to find an optimal set of assets to invest on, as well as to determine the optimal investment for each asset. This optimal selection and weighting of assets is a multi-objective problem where total profit of investment has to be maximized and total risk is to be minimized. In this paper the portfolio optimization problem is solved using three different multi-objective...
In the process of solving multi-objective Pareto solution, the search ability in total area and the convergence characteristics can be reinforced by self-adjusting of aberrance probability in offspring evolution. Comparing with the typical hybrid genetic algorithm, the more effective optimization convergence can be obtained by using the improved hybrid genetic algorithm in solution for optimization...
A multiuser detection based on multi-objective optimization-genetic algorithm (MOO-GA) is proposed for the space-time block coded-multicarrier code-division multiple-access (STBC-MC-CDMA) systems. Due to the spatial diversity, the signals received at the different antennas are faded independently, resulting in an independent log-likelihood function (LLF) for each antenna. To resolve the multi-objective...
The genetic algorithm is used to solve the multi-objective networks design problem that requires selecting a best route to make a balance with cost and delay of the route. Firstly, the mathematical model of the problem is given, then the nondominated sorting generate algorithm is used to solve the model. The algorithm uses coding method with integer to form chromosomes and an initial population is...
Solving multi-objective optimization problem using evolutionary algorithm has attracted much attentions and the great progresses have been made in the past decades. The whole history of the research on multi-objective evolutionary algorithm (MOEA) is divided into three periods. After the features of the researches of MOEA and the research achievements are briefly reviewed, the new progresses of MOEA...
An evolvable hardware structure and design method on an analogue evolvable trans-conductance filter was presented. Its own technical parameters could be changed with external environmentpsilas real-time changing. The filter has the very good adaptive ability and certain fault-tolerant ability. An improved parallel genetic algorithm with migration strategy based on parallel crossover migration was...
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