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Table 1 Cost-time-quality matrix

From: Genetic algorithm based hybrid approach to solve fuzzy multi-objective assignment problem using exponential membership function

Worker (i)

Job (j)

Job-1

Job-2

Job-3

Job-4

Job-5

Job-6

Worker-1

\(c_{ij}\)

(4, 6, 8)

(3, 4, 6)

(4, 5, 8)

(6, 8, 11)

(7, 10, 14)

(4, 6, 7)

\(t_{ij}\)

(2, 4, 5)

(16, 20, 24)

(7, 9, 12)

(2, 3, 5)

(5, 8, 10)

(7, 9, 12)

\(q_{ij}\)

(0, 1, 3)

(1, 3, 5)

(0, 1, 3)

(0, 1, 3)

(0, 1, 3)

(3, 5, 7)

Worker-2

\(c_{ij}\)

(4, 6, 7)

(4, 5, 7)

(5, 6, 9)

(3, 5, 7)

(6, 9, 11)

(6, 8, 11)

\(t_{ij}\)

(4, 6, 9)

(15, 18, 22)

(6, 8, 12)

(5, 7, 10)

(14, 17, 20)

(6, 8, 10)

\(q_{ij}\)

(1, 3, 5)

(3, 5, 7)

(1, 3, 5)

(3, 5, 7)

(5, 7, 9)

(3, 5, 7)

Worker-3

\(c_{ij}\)

(8, 11, 14)

(5, 7, 9)

(2, 4, 6)

(5, 8, 12)

(2, 3, 4)

(3, 4, 6)

\(t_{ij}\)

(2, 3, 4)

(6, 8, 10)

(17, 20, 24)

(5, 7, 10)

(12, 15, 18)

(5, 7, 10)

\(q_{ij}\)

(0, 1, 3)

(5, 7, 9)

(3, 5, 7)

(1, 3, 5)

(3, 5, 7)

(5, 7, 9)

Worker-4

\(c_{ij}\)

(7, 9, 12)

(7, 10, 12)

(6, 8, 11)

(4, 6, 8)

(8, 10, 12)

(3, 4, 6)

\(t_{ij}\)

(10, 12, 16)

(10, 13, 16)

(12, 14, 18)

(4, 6, 9)

(7, 9, 12)

(8, 10, 14)

\(q_{ij}\)

(3, 5, 7)

(7, 9, 10)

(1, 3, 5)

(3, 5, 7)

(1, 3, 5)

(1, 3, 5)

Worker-5

\(c_{ij}\)

(3, 4, 6)

(4, 6, 8)

(5, 7, 10)

(7, 9, 12)

(6, 8, 12)

(5, 7, 10)

\(t_{ij}\)

(7, 9, 12)

(5, 8, 11)

(5, 7, 10)

(11, 14, 18)

(3, 5, 8)

(7, 9, 12)

\(q_{ij}\)

(1, 3, 5)

(7, 9, 10)

(5, 7, 9)

(3, 5, 7)

(1, 3, 5)

(1, 3, 5)

Worker-6

\(c_{ij}\)

(2, 3, 4)

(4, 5, 7)

(8, 11, 15)

(8, 10, 13)

(9, 12, 15)

(6, 8, 12)

\(t_{ij}\)

(14, 17, 21)

(10, 13, 16)

(2, 3, 5)

(3, 5, 8)

(10, 13, 17)

(5, 7, 10)

\(q_{ij}\)

(1, 3, 5)

(1, 3, 5)

(3, 5, 7)

(5, 7, 9)

(3, 5, 7)

(5, 7, 9)