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Dynamic multiobjective optimization problems (DMOPs) bring more challenges for multiobjective evolutionary algorithm (MOEA) due to its time-varying characteristic. To handle this kind of DMOPs, this paper presents a dynamic MOEA with multiple response strategies based on linear environment detection, called DMOEA-LEM. In this approach, different types of environmental changes are estimated and then the corresponding response strategies are activated to generate an efficient initial population for the new environment. DMOEA-LEM not only detects whether the environmental changes but also estimates the types of linear changes so that different prediction models can be selected to initialize the population when the environmental changes. To study the performance of DMOEA-LEM, a large number of test DMOPs are adopted and the experiments validate the advantages of our algorithm when compared to three state-of-the-art dynamic MOEAs.

The wettability and surface free energy of diamonds are crucial for their applications. In this study, polycrystalline boron-doped diamond (PBDD) films with different boron doping concentrations were prepared, and the effect of the boron doping concentration on the wettability and surface free energy (SFE) of the film was investigated. The SFEs of the PBDD films were investigated by employing the surface tension component approach and the equation-of-state approach. The investigation suggested that the alternative formulation of Berthelot’s rule, the Lifshitz-van der Waals/acid-base (van Oss) approach, and the Owens-Wendt-Kaelble approach were suitable for estimating the SFEs of PBDD films, whereas the Fowkes approach, Berthelot’s (geometric mean) combining rule, and Antonow’s rule could not provide reliable results. Results showed that the SFEs of PBDD films increased with increasing boron doping concentration, and the SFEs were 43.26–49.66 mJ/m2 (Owens-Wendt-Kaelble approach), 42.89–52.26 mJ/m2 (Lifshitz-van der Waals/acid-base), and 44.38–48.73 mJ/m2 (alternative formulation of Berthelot’s rule). This study also provides a reference for the application of empirical and physics-based semi-empirical approaches to SFE estimation.