Solving single batch-processing machine problems using an iterated heuristic

Wang, Huimei

doi:10.1080/00207543.2010.518995

Cited by 20 publications

(5 citation statements)

References 26 publications

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“…The work in Jolai Ghazvini and Dupont (1998) and a modified version of the genetic algorithm presented in Damodaran et al (2006) have been used as benchmark procedures for the hybrid max-min ant system presented in Rafiee Parsa et al (2016). Different objective functions dealing with tardiness and lateness have also been addressed (e.g., Wang 2011;Malapert et al 2012;Kosch and Beck 2014;Cabo et al 2015).…”

Section: Introductionmentioning

confidence: 99%

Column generation for minimizing total completion time in a parallel-batching environment

Alfieri

Druetto

Grosso

et al. 2021

J Sched

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This paper deals with the $$1|{p-\text {batch}, s_j\le b}|\sum C_j$$ 1 | p - batch , s j ≤ b | ∑ C j scheduling problem, where jobs are scheduled in batches on a single machine in order to minimize the total completion time. A size is given for each job, such that the total size of each batch cannot exceed a fixed capacity b. A graph-based model is proposed for computing a very effective lower bound based on linear programming; the model, with an exponential number of variables, is solved by column generation and embedded into both a heuristic price and branch algorithm and an exact branch and price algorithm. The same model is able to handle parallel-machine problems like $$Pm|{p-\text {batch}, s_j\le b}|\sum C_j$$ P m | p - batch , s j ≤ b | ∑ C j very efficiently. Computational results show that the new lower bound strongly dominates the bounds currently available in the literature, and the proposed heuristic algorithm is able to achieve high-quality solutions on large problems in a reasonable computation time. For the single-machine case, the exact branch and price algorithm is able to solve all the tested instances with 30 jobs and a good amount of 40-job examples.

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Section: Introductionmentioning

confidence: 99%

Column generation for minimizing total completion time in a parallel-batching environment

Alfieri

Druetto

Grosso

et al. 2021

J Sched

View full text Add to dashboard Cite

show abstract

“…The work in Jolai Ghazvini and Dupont (1998) and a modified version of the genetic algorithm presented in Damodaran et al (2006) have been used as benchmark procedures to the hybrid max-min ant system presented in Rafiee Parsa et al (2016). Different objective functions dealing with tardiness and lateness have been also addressed (e.g., Wang (2011), Malapert et al (2012) and Cabo et al (2015)).…”

Section: Introductionmentioning

confidence: 99%

A solution procedure for minimizing total completion time in a parallel-batching environment

Alfieri,

Druetto,

Grosso

et al. 2020

Preprint

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In many manufacturing processes, batch processing is frequently needed for capacity reasons. This applies both to parallel and serial batching. However, while the serial batch processing is largely studied in the literature, as it is related to the setup issues, the parallel batch processing is less investigated. In parallel batching, the manufacturing facility (e.g., ovens for burn-in operations) is able to accommodate, and process, several parts at the same time and not to exploit such ability leads to a reduction in the capacity of the manufacturing facility itself, which will be able to process less parts per time unit. In this paper, the scheduling problem in batch processing environments is considered. Specifically a column generation algorithm is proposed for parallel batching in both single machine and parallel machine layouts. Numerical results show that the proposed algorithm is able to achieve good solutions in reasonable computation time due to the use of a new developed lower bound much stronger than the literature available lower bounds.

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“…Kashan and Karimi [ 16 ] developed two versions of an ant colony optimization (ACO) framework under the situation considered in Koh et al [ 9 ]. Chou and Wang [ 17 ], Mathirajan et al [ 18 ], and Wang [ 19 ] proposed a hybrid GA, SA, and iterated heuristic for the objective of the total weighted tardiness, respectively. Husseinzadeh Kashan et al [ 20 ] considered bicriteria scheduling for the simultaneous minimization of the makespan and maximum tardiness.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Metaheuristics for Solving a Fuzzy Single Batch-Processing Machine Scheduling Problem

Molla‐Alizadeh‐Zavardehi

Tavakkoli–Moghaddam

Lotfı

2014

The Scientific World Journal

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This paper deals with a problem of minimizing total weighted tardiness of jobs in a real-world single batch-processing machine (SBPM) scheduling in the presence of fuzzy due date. In this paper, first a fuzzy mixed integer linear programming model is developed. Then, due to the complexity of the problem, which is NP-hard, we design two hybrid metaheuristics called GA-VNS and VNS-SA applying the advantages of genetic algorithm (GA), variable neighborhood search (VNS), and simulated annealing (SA) frameworks. Besides, we propose three fuzzy earliest due date heuristics to solve the given problem. Through computational experiments with several random test problems, a robust calibration is applied on the parameters. Finally, computational results on different-scale test problems are presented to compare the proposed algorithms.

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Solving single batch-processing machine problems using an iterated heuristic

Cited by 20 publications

References 26 publications

Column generation for minimizing total completion time in a parallel-batching environment

Column generation for minimizing total completion time in a parallel-batching environment

A solution procedure for minimizing total completion time in a parallel-batching environment

Hybrid Metaheuristics for Solving a Fuzzy Single Batch-Processing Machine Scheduling Problem

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