Complexity

Research Article

Optimal Allocation Method of Discrete Manufacturing Resources for Demand Coordination between Suppliers and Customers in a Fuzzy Environment

Table 4

The transformation of trapezoid fuzzy numbers for language evaluation (one MRD’s example).
Manufacturing units
(0.692, 0.769, 1, 1)(0.385, 0.462, 1, 1)(0.231, 0.308, 0.538, 0.615)(0.385, 0.462, 0.692, 0.769)
(0.385, 0.462, 1, 1)(0.077, 0.154, 0.538, 0.615)(0.385, 0.462, 1, 1)(0.385, 0.462, 1, 1)
(0.385, 0.462, 1, 1)(0, 0, 0.538, 0.615)(0.385, 0.462, 1, 1)(0, 0, 0.846, 0.923)
(0.077, 0.154, 0.538, 0.615)(0.692, 0.769, 1, 1)(0.077, 0.154, 0.538, 0.615)(0, 0, 0.538, 0.615)
(0.385, 0.462, 0.692, 0.769)(0.385, 0.462, 1, 1)(0.692, 0.769, 1, 1)(0.077, 0.154, 0.846, 0.923)
(0.385, 0.462, 0.846, 0.923)(0.077, 0.154, 0.538, 0.615)(0.385, 0.462, 1, 1)(0.538, 0.615, 0.846, 0.923)
(0.385, 0.462, 0.846, 0.923)(0, 0, 0.385, 0.462)(0.385, 0.462, 1, 1)(0, 0, 0.538, 0.615)
(0.385, 0.462, 1, 1)(0.385, 0.462, 0.846, 0.923)(0.077, 0.154, 0.538, 0.615)(0.077, 0.154, 0.692, 0.769)
(0.692, 0.769, 1, 1)(0, 0, 0.538, 0.615)(0.385, 0.462, 0.692, 0.769)(0, 0, 0.538, 0.615)
(0.077, 0.154, 0.538, 0.615)(0.692, 0.769, 1, 1)(0.385, 0.462, 0.846, 0.923)(0, 0, 0.538, 0.615)
(0.385, 0.462, 1, 1)(0.385, 0.462, 1, 1)(0.385, 0.462, 0.846, 0.923)(0.385, 0.462, 1, 1)
(0.077, 0.154, 1, 1)(0.385, 0.462, 1, 1)(0.077, 0.154, 0.692, 0.769)(0.385, 0.462, 1, 1)
(0, 0, 0.231, 0.308)(0.077, 0.154, 0.538, 0.615)(0.385, 0.462, 1, 1)(0, 0, 0.538, 0.615)
(0.077, 0.154, 0.538, 0.615)(0.385, 0.462, 0.692, 0.769)(0.385, 0.462, 1, 1)(0.692, 0.769, 1, 1)
(0.692, 0.769, 1, 1)(0.385, 0.462, 0.846, 0.923)(0.692, 0.769, 1, 1)(0.385, 0.462, 1, 1)
(0.692, 0.769, 1, 1)(0.385, 0.462, 0.846, 0.923)(0.231, 0.308, 0.692, 0.769)(0.077, 0.154, 0.538, 0.615)
(0.538, 0.615, 0.846, 0.923)(0.385, 0.462, 1, 1)(0.077, 0.154, 1, 1)(0, 0, 0.385, 0.462)
(0, 0, 0.231, 0.308)(0.692, 0.769, 1, 1)(0.385, 0.462, 1, 1)(0.385, 0.462, 0.846, 0.923)
(0.385, 0.462, 0.846, 0.923)(0.692, 0.769, 1, 1)(0, 0, 0.538, 0.615)(0, 0, 0.538, 0.615)
(0.077, 0.154, 0.849, 0.923)(0.692, 0.769, 1, 1)(0, 0, 0.538, 0.615)(0.692, 0.769, 1, 1)
(0, 0, 0.538, 0.615)(0, 0, 0.538, 0.615)(0.692, 0.769, 1, 1)(0.385, 0.462, 1, 1)
(0.538, 0.615, 0.846, 0.923)(0.077, 0.154, 0.538, 0.615)(0.385, 0.462, 1, 1)(0.385, 0.462, 1, 1)
(0.385, 0.462, 1, 1)(0.385, 0.462, 1, 1)(0.077, 0.154, 0.538, 0.615)(0.077, 0.154, 0.538, 0.615)
(0, 0, 0.538, 0.615)(0.692, 0.769, 1, 1)(0, 0, 0.385, 0.462)(0.385, 0.462, 0.692, 0.769)
(0.385, 0.462, 1, 1)(0.692, 0.769, 1, 1)(0.385, 0.462, 0.846, 0.923)(0.385, 0.462, 0.846, 0.923)
(0, 0, 0.538, 0.615)(0, 0, 0.538, 0.615)(0.385, 0.462, 1, 1)(0.385, 0.462, 0.846, 0.923)
(0.692, 0.769, 1, 1)(0.538, 0.615, 0.846, 0.923)(0.385, 0.462, 1, 1)(0.692, 0.769, 1, 1)
(0.385, 0.462, 1, 1)(0.692, 0.769, 1, 1)(0.077, 0.154, 0.538, 0.615)(0.385, 0.462, 0.846, 0.923)
(0.077, 0.154, 0.538, 0.615)(0.692, 0.769, 1, 1)(0.077, 0.154, 0.692, 0.769)(0.385, 0.462, 1, 1)
(0, 0, 0.385, 0.462)(0.538, 0.615, 0.846, 0.923)(0.385, 0.462, 1, 1)(0, 0, 0.538, 0.615)
(0.385, 0.462, 0.846, 0.923)(0, 0, 0.231, 0.308)(0.077, 0.154, 0.846, 0.923)(0.077, 0.154, 0.538, 0.615)
Expectation value(0.385, 0.462, 0.538, 0.615)(0.538, 0.615, 0.692, 0.769)(0.692, 0.769, 0.846, 0.923)(0.385, 0.462, 0.538, 0.615)