### Abstract

This paper studies a sequence-dependent scheduling problem incorporating order delivery, motivated by satellite imaging scheduling. A set of jobs is to be processed on a single machine and each job belongs to a specific group. The completion time of a group is the moment when all jobs belonging to this group are completed. The problem is to determine a processing sequence of the jobs such that the sum of weighted completion times over all groups is minimized. We present a binary integer program to formulate the studied problem and then develop an O(n
^{2}
2
^{n}
) dynamic programming algorithm for determining optimal solutions. To produce approximate solutions within an acceptable time, we design a tabu search algorithm, an iterated local search algorithm and a genetic algorithm. Computational experiments are conducted to study the performance of the integer program and the solution algorithms. Numerical statistics suggest that the binary integer program can reach optimal solutions faster than the integer program existing in the literature, and the iterated local search algorithm outperforms other approaches when the number of jobs increases.

Original language | English |
---|---|

Pages (from-to) | 58-71 |

Number of pages | 14 |

Journal | Applied Mathematics and Computation |

Volume | 222 |

DOIs | |

State | Published - 19 Aug 2013 |

### Keywords

- Meta-heuristics
- Order delivery
- Satellite imaging scheduling
- Sequence-dependent setup
- Total weighted completion time

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## Cite this

*Applied Mathematics and Computation*,

*222*, 58-71. https://doi.org/10.1016/j.amc.2013.06.087