## 2 Related Work  
Subjective weights are in good accordance with the basic cognition of experts to robustness criteria; however, the information contained in the robustness criteria cannot be considered by the experts when they are giving the subjective weights. Objective weights have strong data theoretical basis; however, they cannot take the experts' experience and judgment into account. Therefore, the combination of subjective and objective weights can take advantage of and overcome the disadvantage of both weighting methods. In this section, the related work on subjective weighting methods, objective weighting methods, and methods of combining subjective and objective weights is reviewed and discussed. Subjective weighting methods mainly include the analytic hierarchy process (AHP) [23], the Delphi method [24], and the expert-evaluation-based method [25]. These methods are effective in reflecting the importance of different criteria because experts are well-experienced in this field, and they can make reasonable judgments according to actual situations. However, individual preferences are inevitably involved in subjective weighting. Thus, in the above methods, the experts are regarded as rational humans, and the evaluation curve is regarded as an expected utility curve. However, a large number of psychological experiments have demonstrated that the actual behaviors of humans do not correspond to the expected utility curve. Due to the bounded rationality of humans, there tends to be risk aversion when the profit probability is relatively high and risk-seeking when there is a rather high loss probability. At the same time, there tends to be risk-seeking when the profit probability is relatively low, and risk aversion when there is a relatively small chance to suffer losses [26]. It can be concluded that human judgments have individual preferences. Prospect theory has established a successful model to simulate the psychological and behavioral characteristics of human beings, which has been widely applied in the field of engineering [27; 28; 29], economics [30; 31; 32], computer science [33; 34; 35], and so on. This provides a convincing explanation of the fact that the results of subjective empowerment do not conform to reality. So, prospect theory is useful to modify the preliminary results obtained by subjective weighting so as to make the evaluation results become \"rational\" ones out of the \"boundedly rational\" ones. By using objective weighting methods, including entropy weight method [36], principal component analysis method [37] as well as standard deviation method [38], the weights of different criteria are calculated according to the amount of information they contain. The three robustness criteria proposed, namely, start time deviation, structural deviation, and completion probability, which can comprehensively evaluate the schedule robustness, are interrelated to some extent. Therefore, it is unreasonable to assign their respective weights without considering their intercriteria correlation. Criteria importance through intercriteria correlation (CRITIC) is an objective weighting method that measures a criterion by considering both the importance itself and the conflict caused by intercriteria correlations [39]. In summary, in the traditional CRITIC method, the intercriteria correlation is determined by the Pearson correlation coefficient function, which reflects the linear correlation. The Copula function is very useful for the analysis of the correlation between variables when it cannot determine whether the correlation between variables is linear or nonlinear. Thus, it can effectively deal with the difficult intercriteria correlation among the three robustness criteria. Therefore, the CRITIC method is improved by introducing the Copula function to replace the Pearson correlation coefficient, and the objective weights that could incorporate both inherent importance and nonlinear intercriteria correlations can be obtained using the Copula-CRITIC method.