S.No. | Measure of Performance | Methods | Reference Numbers of Articles |

1 | C | Theoretical study | [3] - [9] |

Mathematical models | [10] - [13] | ||

Exact algorithms | [14] - [18] | ||

Heuristics | [1] [19] - [50] | ||

Genetic algorithms | [51] - [58] | ||

Tabu search algorithms | [59] [60] | ||

Simulated annealing algorithms | [61] | ||

ACO algorithms | [62] [63] | ||

Bee colony optimization algorithms | [64] [65] | ||

Hybrid algorithms | [66] - [69] | ||

2 | ―Minimize the sum of completion times of all the jobs | Exact algorithms | [70] |

Heuristics | [71] - [79] | ||

Tabu search algorithms | [80] | ||

Particle swarm optimization algorithm | [65] | ||

Hybrid algorithms | [81] | ||

Multiple algorithms | [82] | ||

Miscellaneous algorithms | [83] | ||

3 | ―Minimize the weighted sum of completion times of all jobs | Heuristics | [84] [85] |

Genetic algorithms | [86] | ||

Particle swam optimization algorithms | [87] | ||

4 | ―Minimize the total tardiness of all jobs | Heuristics | [88] [89] |

5 | ―Minimize weighted total tardiness | Mathematical models | [91] |

Heuristics | [92] | ||

Simulated annealing | [93] | ||

6 | ―Minimize the number of late jobs | Heuristics | [88] |

7 | ―Minimize the weighted sum of late jobs | Heuristics | [94] |

8 | L | Heuristics | [90] |

9 | Miscellaneous measures and theory |
| [2] [95] - [101] |