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They are called the basic data of a multi-criterion problem (Brans and Mareschal 1994a, b; Brans et al. 1984).
A multi-criterion problem is mathematically defined as (Brans and Mareschal 1994 a, b; Brans et al. 1984): Max g 1 a, g 1 a, …, g i a, …, g k a ⋅ | ⋅ ⋅ a є A, Open image in new window (8).
Process optimisation is often a multi-criteria problem.
They are being judged on the usual startup criteria: Problem, Solution, Technology, Team, Market, Traction, and Future prospects.
By considering a scalarizing method, the bi-criteria problem is converted to a single objective problem.
By introducing the expectation level, the bi-criteria problem is converted into a single-objective problem.
Eq. (1) shows the linear convex combination of the dual criteria problem.
Secondly, it proposes an AHP-MCR approach to dealing with the dynamic context criteria problem.
To address the bi-criteria problem, a Pareto-based ant colony optimization (PACO) algorithm is proposed.
The ɛ-constraint method is used to deal with the multi-criteria problem.
The design of such bearings is a multi-variable, multi-criteria problem.
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