As a main result, the paper gives a set of solutions for the reconciled data under an interval form and not only one solution as is the case with classical approaches.
Given a set of possible solutions, the solution A dominates B, if the value of at least one objective in A is better than the corresponding objective value in B and the values of the remaining objectives in A are at least equal to the corresponding values in B. A is non-dominated if it is not dominated by any other solution.
Given a set of possible solutions, the solution A dominates B if, the value of at least one objective in A is better than the corresponding objective value in B, and the values of the remaining objectives in A are at least equal to the corresponding values in B. We observe that the generation of test data sets is a multi-objective problem, impacted by many factors.
If only ω, k, h, the Reynolds Re, the Prandtl number Pr, and the subspaces (X_{h}), (M_{h}), and (W_{h}) are given, a set of SMFE solutions ({boldsymbol {u}_{h}^{n},p_{h}^{n},Q_{h}^{n}}_{n=1}^{n}) is acquired by Problem III.
Therefore, given a set of seaports, this paper aims to provide solutions for which seaports should be retrofitted in order to minimize the damage loss due to unpredictable disasters.
This fuzzy-based approach in robust design is able to give a set of Pareto optimal solutions in terms of structural efficiency and sensitivities regarding uncertainty, and represents a suitable tool in supporting the decision maker.
Theorem 3.1 gives a set of sufficient conditions on the nonexistence of solutions of BVP (1.5).
The moment you move to a platform play across these various business units and business properties, it gives you the opportunity to launch a set of solution services off these platforms.
Following this approach, the environmental and the economic performance are quantified separately as two different objectives, and the final result is given by a set of Pareto optimal solutions.
These contradictory requirements of different objective functions give rise to a set of possible solutions call pareto optimal solutions instead of a single possible solution.
