However, the different relationships among these followers might force the leader to use multiple different processes in deriving an optimal solution for leader decision making.
The proposed system employs the TOPSIS (Technique of ranking Preferences by Similarity to the Ideal Solution) multiple criteria decision making method to solve materials selection and optimisation problem.
A case of study, considering a bi-layer scenario, is presented in order to validate the proposal, which showed to be able to provide good quality solutions for supporting decision making.
In the literature, three general categories of decision making solutions can be observed: solutions based on network conditions, multiple attribute algorithms, and artificial intelligence.
It will be shown that several Pareto optimal solutions close to an aspiration level of decision maker can be listed up as candidates of a final decision making solution by the proposed method.
In the decision making solution, the algorithm adjustment and parameter selection of TOPSIS are identified and tested based on three parameters, namely, normalisation, separation and contexts.
Learning-based interactive methods provide a suitable solution for collaborative participatory decision making in a dynamic decision environment such as the implementation of a new directive.
To deal with this problem, a model-driven solution for real-time decision making in event-driven SOAs is proposed and conducted in this paper.
By comparing the deviation index of each final optimal solution from the ideal solution, it is shown that the multi-objective optimization can lead to a more desirable design compared to the single-objective optimizations, and the final optimal solution selected by TOPSIS decision making presents superior performance.
Decision aids are a potential solution to improve ICD decision making [ 41].
Decision aids offer promise as a practical solution to improve patient decision making about coronary heart disease (CHD) prevention medications and help patients choose medications to which they are likely to adhere.
