No-wait flowshop scheduling problem with two criteria; total tardiness and makespan

We consider a no-wait m-machine flowshop scheduling problem which is common in different manufacturing industries such as steel, pharmaceutical, and chemical. The objective is to minimize total tardiness since it minimizes penalty costs and loss of customer goodwill. We also consider the performance measure of total completion time which is significant in environments where reducing holding cost is important. We consider both performance measures with the objective of minimizing total tardiness subject to the constraint that total completion time is bounded. Given that the problem is NP-hard, we propose an algorithm. We conduct extensive computational experiments to compare the performance of the proposed algorithm with those of three well performing benchmark algorithms in the literature. Computational results indicate that the proposed algorithm reduces the error of the best existing benchmark algorithm by 88% under the same CPU times. The results are confirmed by extensive statistical analysis. Specifically, ANOVA analysis is conducted to justify the difference between the performances of the algorithms, and a test of hypothesis is performed to justify that the proposed algorithm is significantly better than the best existing benchmark algorithm with a significance level of 0.01.

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No-wait flowshop scheduling problem with separate setup times to minimize total tardiness subject to makespan

Applied Mathematics and Computation ◽

10.1016/j.amc.2019.124688 ◽

2020 ◽

Vol 365 ◽

pp. 124688 ◽

Cited By ~ 4

Author(s):

Ali Allahverdi ◽

Harun Aydilek ◽

Asiye Aydilek

Keyword(s):

Setup Times ◽

Total Tardiness ◽

Scheduling Problem ◽

Flowshop Scheduling ◽

No Wait ◽

Flowshop Scheduling Problem

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Minimizing total tardiness in no-wait flowshops

Foundations of Computing and Decision Sciences ◽

10.2478/v10209-011-0009-6 ◽

2012 ◽

Vol 37 (3) ◽

pp. 149-162 ◽

Cited By ~ 16

Author(s):

Tariq Aldowaisan ◽

Ali Allahverdi

Keyword(s):

Genetic Algorithms ◽

Computation Time ◽

Total Tardiness ◽

Computational Experiments ◽

Scheduling Problem ◽

Dispatching Rule ◽

Flowshop Scheduling ◽

No Wait ◽

Flowshop Scheduling Problem ◽

Better Than

AbstractWe address the m-machine no-wait flowshop scheduling problem; where the objective is to minimize total tardiness. To the best of our knowledge, the considered problem has not been addressed so far. We propose heuristic solutions since the problem is NP-hard. Initially, we consider a number of dispatching rules commonly used for the considered objective in other scheduling environments. We identify through computational experiments the best performing dispatching rule; and then propose simulated annealing (SA) and genetic algorithms (GA) by using the best performing dispatching rule as an initial solution. This achieves at least 50% improvement in the SA and GA performances. Next, we propose enhanced versions of SA and GA and show through computational experiments that the enhanced versions provide over 90% further improvement. The performance of enhanced GA is slightly better than that of enhanced SA; however, the computation time of enhanced GA is about 10 times that of enhanced SA. Therefore, we conclude that the enhanced SA outperforms the enhanced GA.

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