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Table 6 Compromised solutions with respect to improvement desired in various objective at confidence level \(\alpha =0.5\) with different shape parameter

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

Case

Obj. function

Bounds

\(\lambda\)

Objective values

Solution variables

(\(Z_{1}, Z_{2}, Z_{3}\))

\(x_{ij}\)

Shape parameter: (−5, −1, −2)

Aspiration level: (0.8, 0.85, 0.7)

1

Cost

\(19 \le z_{11} \le 36.5\),

0.8255

(30.5, 35, 42.5),

\(x_{11}, x_{23}, x_{36}, x_{44}, x_{55}, x_{62}\)

\(23 \le z_{12} \le 42\),

(36.5, 43, 51.5),

\(28 \le z_{13} \le 50.5\)

(16.5, 22, 28)

2

Quality

\(7.5 \le z_{31} \le 11\),

0.7311

(32.5, 37, 45)

\(x_{11}, x_{14}, x_{23}, x_{46}, x_{55}, x_{62}\)

\(12 \le z_{32} \le 16\),

(37, 43, 51.5),

\(18 \le z_{33} \le 22\)

(9, 14, 20)

3

Quality

\(7.5 \le z_{31} \le 9\),

0.8644

(36, 41, 49.5)

\(x_{13}, x_{14}, x_{31}, x_{46}, x_{55}, x_{62}\)

\(12 \le z_{32} \le 14\),

(37.5, 43, 51),

\(18 \le z_{33} \le 20\)

(7.5, 12, 18)

Aspiration level: (0.9, 0.7, 0.8)

1

Cost

\(19 \le z_{11} \le 32.5\),

0.7550

(26, 30, 36),

\(x_{11}, x_{23}, x_{35}, x_{36}, x_{44}, x_{62}\)

\(23 \le z_{12} \le 37\),

(46, 53, 61.5),

\(28 \le z_{13} \le 45\)

(18.5, 24, 30)

2

Quality

\(7.5 \le z_{31} \le 9\),

0.8644

(36, 41, 49.5)

\(x_{13}, x_{14}, x_{31}, x_{46}, x_{55}, x_{62}\)

\(12 \le z_{32} \le 14\),

(37.5, 43, 51),

\(18 \le z_{33} \le 20\)

(7.5, 12, 18)

Aspiration level: (0.7, 0.8, 0.9)

1

Cost

\(19 \le z_{11} \le 36\),

0.8142

(29.5, 34, 41.5),

\(x_{11}, x_{23}, x_{24}, x_{46}, x_{55}, x_{62}\)

\(23 \le z_{12} \le 41,\)

(40.5, 47, 56),

\(28 \le z_{13} \le 49.5\)

(12.5, 18, 24)

Shape parameter: (−2, −5, −1)

Aspiration level: (0.8, 0.85, 0.7)

1

Cost

\(19 \le z_{11} \le 25.5\),

0.8187

(21.5, 25, 30.5),

\(x_{13}, x_{24}, x_{35}, x_{46}, x_{61}, x_{62}\)

\(23 \le z_{12} \le 29\),

(63.5, 71, 81),

\(28 \le z_{13} \le 35.5\)

(14.5, 20, 26)

2

Time

\(24 \le z_{21} \le 51.5\),

0.8048

(32.5, 37, 45),

\(x_{11}, x_{14}, x_{23}, x_{46}, x_{55}, x_{62}\)

\(29 \le z_{22} \le 58\),

(37, 43, 51.5),

\(35.5 \le z_{23} \le 67.5\)

(9, 14, 20)

Shape parameter: (−1, −2, −5)

Aspiration level: (0.7, 0.8, 0.85)

1

Quality

\(7.5 \le z_{31} \le 15\),

0.8124

(28.5, 33, 40.5),

\(x_{11}, x_{13}, x_{24}, x_{46}, x_{55}, x_{62}\)

\(12 \le z_{32} \le 20\),

(41.5, 48, 56.6),

\(18 \le z_{33} \le 26\)

(9, 14, 20)

2

Quality

\(7.5 \le z_{31} \le 11\),

0.7199

(31, 36, 44.5),

\(x_{11}, x_{13}, x_{34}, x_{46}, x_{55}, x_{62}\)

\(12 \le z_{32} \le 16\),

(41.5, 48, 56.6),

\(18 \le z_{33} \le 22\)

(9, 14, 20)

Aspiration level: (0.8, 0.85, 0.7)

1

Quality

\(7.5 \le z_{31} \le 17\),

0.7848

(26.5, 30, 36.5),

\(x_{14}, x_{23}, x_{35}, x_{46}, x_{51}, x_{62}\)

\(12 \le z_{32} \le 22\),

(51.5, 58, 67.5),

\(18 \le z_{33} \le 28\)

(12.5, 18, 24)