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中文摘要：
多目标寻优中,决策者通常只对目标空间某个区域内的优解感兴趣,希望寻优结果为满足偏好要求的Pareto优解。因此提出基于偏好的多目标免疫算法,在优化过程中根据偏好信息来引导寻优方向。将此算法应用在电站锅炉排放的LS-SVM建模参数寻优中,仿真结果表明,该方法能够有效地获得期望区域内的Pareto优解,方便决策者做出决策,且在决策者偏好发生改变时,算法能够做出快速响应。
英文摘要：
It is generally admitted that the decision makers（DM） focus solely on a special space while facing a multi-objective optimization problem,thus a preference-based immune multi-objective optimization algorithm（PIMOA） for Pareto optimal solutions is presented in this paper.After the PIMOA method is applied in the parameter optimization of LS-SVM modeling for boiler emission,the simulation result shows that it can deliver more desired Pareto optimal solutions within the preferred region for the DM and it can respond swiftly when the DM changes their preferences.
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