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Then we study the on-line problem with objective minimization of the sum of completion times of the rides.
We study the single machine scheduling problem with the objective of minimizing the weighted sum of completion times.
We study scheduling problems when jobs can be split and a setup is required before processing each part, to minimize the weighted sum of completion times.
Sung and Kim [24] developed a branch-and-bound algorithm for two stage multiple assembly flowshop to minimize the sum of completion times.
The objective of the first stage is to minimize the inventory cost measured by the sum of completion time, and that of the second stage is to minimize the tardiness cost and the resequencing cost in the buffer.
The set of hard problems includes different variations where the objective functions of the two agents are either minimizing the weighted sum of completion times or the weighted number of tardy jobs.
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The objective is to find a schedule that minimizes the sum of weighted completion times of the jobs.
For a given number of jobs, we want to choose batch sizes so as to minimize the sum of the completion times of the jobs.
The problem is to determine a processing sequence of the jobs such that the sum of weighted completion times over all groups is minimized.
Let F ( j ) denote the minimum the sum of the completion times for the j-jobs batching problem containing jobs 1, …, j.
This paper presents a new, carefully designed algorithm for five bi-objective permutation flow shop scheduling problems that arise from the pairwise combinations of the objectives (i) makespan, (ii) the sum of the completion times of the jobs, and (iii) both, the weighted and non-weighted total tardiness of all jobs.
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