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In this paper, we consider the problem of scheduling a job shop (JSS) where set-up times are sequence-dependent (SDST) to minimize the maximum completion times of operations or makespan.
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The objective is to minimize the maximum completion time.
The objective is to minimize the makespan, i.e. the maximum completion time of the jobs.
In this paper, a self-guided differential evolution with neighborhood search (NS-SGDE) is presented for the PFSSP with the objectives of minimizing the maximum completion time.
In such a paper, we address the Distributed Permutation Flowshop Scheduling Problem (DPFSP) with an artificial chemical reaction metaheuristic which objective is to minimize the maximum completion time.
We provide a mathematical model for the problem and present an improved migrating birds optimization (IMMBO) to minimize the maximum completion time or makespan.
The objective is to minimize the maximum completion time (called makespan) while scheduling independent jobs in parallel on machines that have different speeds.
Performance criteria considered are the maximum completion time so called makespan, the total workload of machines and the workload of the critical machine.
Three minimization objectives – the maximum completion time (makespan), the total workload of machines and the workload of the critical machine are considered simultaneously.
Minimization of the following three objective functions are considered in this paper: maximum completion time, workload of the most loaded machine and total workload of all machines.
Liu et al., [15] solved flow shop scheduling with limited buffers with an effective hybrid PSO-based algorithm to minimize the maximum completion time.
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