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Dynamic multiobjective optimization problem (DMOP) is a class of complex dynamic optimization problem (DOP), its widely exists in many real-world problems. Firstly, an core estimation of distribution model which used to approximately estimate the Pareto solution in the next environment is given, when a change in the environment is detected, the algorithm uses the collected information from the previous...
By means of analyzing Yong's minimax portfolio selection model, a novel risk function is introduced with risk measure considering risk and extra return factors. The risk factor can tune the effects of asset yield on the investment decision, and the extra return factor can control the effects of assets portfolio's margin on the investment decision. Furthermore, an assets portfolio optimization model...
In this paper, we establish a rate duality between the forward and reverse links of MIMO interference channel, where the reverse links are obtained by exchanging the roles of transmitters and receivers in the forward links, and the corresponding channel matrices are conjugate transpose of the forward channel matrices. Since the capacity region for general interference channel is unknown, we show that...
In a communication network, it is often impractical for each node to learn the global channel knowledge (network connectivity and channel state information of each link). In this paper, we address distributed rate optimization for Time-Division Duplex (TDD) Multiple-Input Multiple-Output (MIMO) networks when part of the local channel knowledge is learned via message passing between each transmitter...
To keep competitive edge in the global market manufacturing enterprises have to enhance their information systems such as ERP with production planning optimization. In this paper in terms of make-to-order discrete manufacturing a segregate framework model is proposed to support the production planning optimization and to integrate with ERP system. This model aims to sufficiently utilize the production...
In this paper, a new evolutionary algorithm (EA) to solve multi-objective constrained optimization problem (MCOP) is proposed. First, the rank of the individual and the scalar constraint violation of the individual are defined. Then, based on the rank and the scalar constraint violation of the individual, a new fitness function and a switch selection operator are presented. Accordingly, when the individuals...
A novel evolutionary algorithm based on the new model for multiobjective optimization problems (MOPs) is presented in this paper. Firstly, we defined two measures, one is the rank variance of population and the other is the U - measure variance of population. The rank variance of population is a measure of the quality of solutions and the U -measure variance of population is a measure of the uniformity...
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