The impact of neighbourhood size on the process of simulated annealing: Computational experiments on the flowshop scheduling problem

1999 ◽  
Vol 37 (1-2) ◽  
pp. 285-288 ◽  
Author(s):  
Jiyin Liu
Keyword(s):  
Simulated Annealing ◽  
Computational Experiments ◽  
Scheduling Problem ◽  
Flowshop Scheduling ◽  
Neighbourhood Size ◽  
Flowshop Scheduling Problem ◽  
The Impact

scholarly journals Three-Machine Flowshop Scheduling Problem to Minimize Total Completion Time with Bounded Setup and Processing Times

2007 ◽  
Vol 1 (2) ◽  
pp. 5-23 ◽  
Author(s):  
Ali Allahverdi
Keyword(s):  
Completion Time ◽  
Computational Experiments ◽  
Total Completion Time ◽  
Scheduling Problem ◽  
Flowshop Scheduling ◽  
Dominance Relations ◽  
Processing Times ◽  
Flowshop Scheduling Problem ◽  
Global And Local ◽  
Local Dominance

The three-machine flowshop scheduling problem to minimize total completion time is studied where setup times are treated as separate from processing times. Setup and processing times of all jobs on all machines are unknown variables before the actual occurrence of these times. The lower and upper bounds for setup and processing times of each job on each machine is the only information that is available. In such a scheduling environment, there may not exist a unique schedule that remains optimal for all possible realizations of setup and processing times. Therefore, it is desired to obtain a set of dominating schedules (which dominate all other schedules) if possible. The objective for such a scheduling environment is to reduce the size of dominating schedule set. We obtain global and local dominance relations for a three-machine flowshop scheduling problem. Furthermore, we illustrate the use of dominance relations by numerical examples and conduct computational experiments on randomly generated problems to measure the effectiveness of the developed dominance relations. The computational experiments show that the developed dominance relations are quite helpful in reducing the size of dominating schedules.

Hybrid Metaheuristics for Solving the Blocking Flowshop Scheduling Problem

2018 ◽  
Vol 36 ◽  
pp. 124-136 ◽  
Author(s):  
Ghita Lebbar ◽  
Abdellah El Barkany ◽  
Abdelouahhab Jabri ◽  
Ikram El Abbassi
Keyword(s):  
Simulated Annealing ◽  
Flow Shop ◽  
Flow Shop Scheduling ◽  
Scheduling Problem ◽  
Flowshop Scheduling ◽  
Hybrid Metaheuristics ◽  
Blocking Flowshop ◽  
Maximum Completion Time ◽  
Flowshop Scheduling Problem ◽  
Makespan Criterion

This paper suggests two evolutionary optimization approaches for solving the blocking flow shop scheduling problem with the maximum completion time (makespan) criterion, namely the genetic algorithm (GA) and the simulated annealing genetic algorithms (SAGA) that combines the simulated annealing (SA) with the (GA), respectively. The considered problem and the proposed algorithms have some parameters to be adjusted through a design of experiments with exorbitant runs. In fact, a Taguchi method is presented to study the parameterization problem empirically. The performance of the proposed algorithms is evaluated by applying it to Taillard’s well-known benchmark problem, the experiment results show that the SA combined with GA method is advanced to the GA and to the compared algorithms proposed in the literature in minimizing makespan criterion. Ultimately, new known upper bounds for Taillard’s instances are reported for this problem, which can be used thereafter as a basis of benchmark in eventual investigations.

Algorithms for four-machine flowshop scheduling problem with uncertain processing times to minimize makespan

2020 ◽  
Vol 54 (2) ◽  
pp. 529-553 ◽  
Author(s):  
Muberra Allahverdi ◽  
Ali Allahverdi
Keyword(s):  
Upper Bounds ◽  
The Other ◽  
Computational Experiments ◽  
Scheduling Problem ◽  
Flowshop Scheduling ◽  
Lower And Upper Bounds ◽  
Significance Level ◽  
Dominance Relations ◽  
Processing Times ◽  
Flowshop Scheduling Problem

We consider the four-machine flowshop scheduling problem to minimize makespan where processing times are uncertain. The processing times are within some intervals, where the only available information is the lower and upper bounds of job processing times. Some dominance relations are developed, and twelve algorithms are proposed. The proposed algorithms first convert the four-machine problem into two stages, then, use the well-known Johnson’s algorithm, known to yield the optimal solution for the two-stage problem. The algorithms also use the developed dominance relations. The proposed algorithms are extensively evaluated through randomly generated data for different numbers of jobs and different gaps between the lower and upper bounds of processing times. Computational experiments indicate that the proposed algorithms perform well. Moreover, the computational experiments reveal that one of the proposed algorithms, Algorithm A7, performs significantly better than the other eleven algorithms for all possible combinations of the number of jobs and the gaps between the lower and upper bounds. More specifically, error percentages of the other eleven algorithms range from 2.3 to 27.7 times that of Algorithm A7. The results have been confirmed by constructing 99% confidence intervals and tests of hypotheses using a significance level of 0.01.

Heuristics for an m-Machine Re-Entrant Permutation Flowshop with the Objective of Total Tardiness

2015 ◽  
Vol 752-753 ◽  
pp. 890-895 ◽  
Author(s):  
Seong Woo Choi
Keyword(s):  
Heuristic Algorithms ◽  
Total Tardiness ◽  
Computational Experiments ◽  
Test Problems ◽  
Scheduling Problem ◽  
Flowshop Scheduling ◽  
Permutation Flowshop ◽  
Flowshop Scheduling Problem ◽  
Flowshop Problem

We focus on an m-machine re-entrant flowshop scheduling problem with the objective of minimizing total tardiness. In the re-entrant flowshop considered here, routes of all jobs are identical as in ordinary flowshops, but the jobs must be processed multiple times on the machines. We present heuristic algorithms, which are modified from well-known existing algorithms for the general m-machine flowshop problem or newly developed in this paper. For evaluation of the performance of the algorithms, computational experiments are performed on randomly generated test problems and results are reported.

scholarly journals Minimizing total tardiness in no-wait flowshops

2012 ◽  
Vol 37 (3) ◽  
pp. 149-162 ◽  
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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