报告题目1：Multicriteria Decision Making based on SMAA-Stochastic Multicriteria Acceptability Analysis
Multicriteria decision making(MCDM) has been widely used in different sectors because real life decision problems generally involve two or more criteria. Majority of MCDM methods rely on decision models that need deterministic weight vectors, which need to be elicited by direct judgment or by some indirect methods. However, this process is highly affected by uncertainties in the criteria values and weightings. Therefore, this paper presents the Stochastic Multicriteria Acceptability Analysis(SMAA) method, which is an increasingly popular MCDM method for problems with significant uncertainty or imprecision in criteria and weights.
报告题目2： Multi-Objective Linear Programming for Large Scale Energy Optimization
In many real-life optimization problems it is necessary to consider simultaneously multiple objectives. The objectives are typically non-commensurate, i.e. there is no unique way to combine them. For example, in the area of energy production, objectives could be to minimize at the same time production costs and different emissions. Because in general no sulution is simultaneously best with respect to all objectives, it is up to the decision maker (DM) how to compromise between them.
报告人: Professor Risto Lahdelma （Aalto University芬兰阿尔托大学）
Dr. Risto Lahdelma, Professor, School of Engineering, Aalto University (芬兰阿尔托大学). Professor Risto Lahdelma's research interests include the following:
Mathematical modelling, simulation, optimization and multicriteria decision support; 2. Applications in energy systems and also other areas such as production planning and environmental problems.