Improved MILP models for two-machine flowshop with batch processing machines

Liao, Ching‐Jong; Liao, Li-Man

doi:10.1016/j.mcm.2008.01.001

Cited by 27 publications

(11 citation statements)

References 6 publications

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“…It was shown that this problem is NP-hard in ordinary sense and three heuristics were presented to minimize this objective. For the same problem, Liao and Liao [23] improved their formulations and Manjeshwar et al [28] and Manjeshwar et al [28] have proposed metaheuristic algorithms. But, as is mentioned, the number of processors in an assembly line varies from one to m. Recently, scheduling problem with batch processors has attracted many researchers in both theoretical and practical areas.…”

Section: Related Literaturementioning

confidence: 99%

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Scheduling of printed circuit board (PCB) assembly systems with heterogeneous processors using simulation-based intelligent optimization methods

Noroozi

Mokhtari

2014

Neural Comput & Applic

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The complexity of printed circuit boards (PCBs), as an important sector of the electronics manufacturing industry, has increased over the last three decades. This paper focuses on a practical application observed at a PCB assembly line of electronics manufacturing facility. It is shown that this problem is equivalent to a flowshop scheduling with multiple heterogeneous batch processors where processors can perform multiple tasks as long as the sizes of jobs in a batch do not violate the processors' capacity. The equivalent problem is mathematically formulated as a mixed integer programming model. Then, a Monte Carlo simulation is incorporated into high-level genetic algorithm-based intelligent optimization techniques to assess the performance of makespan-oriented system under uncertain processing times. At each iteration of algorithm, the output of simulator is used by optimizers to provide online feedbacks on the progress of the search and direct the search toward a promising solution zone. Furthermore, various parameters and operators of the algorithm are discussed and calibrated by means of Taguchi statistical technique. The result of extensive computational experiments shows that the solution approach gives high-quality solutions in reasonable computational time.

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Section: Related Literaturementioning

confidence: 99%

“…For a flowshop with two batch processors, Damodaran and Srihari [8] presented a mixed integer formulations for the zero and infinite buffer capacity situations. Afterward, Liao and Liao [23] improved their models and Manjeshwar et al [28] proposed a SA for solving the case of infinite buffer capacity.…”

Section: Related Literaturementioning

confidence: 99%

Scheduling of printed circuit board (PCB) assembly systems with heterogeneous processors using simulation-based intelligent optimization methods

Noroozi

Mokhtari

2014

Neural Comput & Applic

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“…Damodaran and Srihari [17] and Liao and Liao [18] presented MIP formulations for the flow shop problem with two batching machines, where solutions are restricted to consistent batches and permutation schedules. In both studies, a binary variable is used which indicates whether or not a batch is assigned to a specific position in the sequence.…”

Section: Mip Formulationsmentioning

confidence: 99%

“…According to (18), lateness is calculated by completion time (C i = t i + p i ) and due date (d i ).…”

Section: Extensionsmentioning

confidence: 99%

MIP formulations and heuristics for solving parallel batching problems

Buscher

Shen

2010

J Syst Sci Complex

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This paper addresses the scheduling problem involving batch processing machines, which is also known as parallel batching in the literature. The presented mixed integer programming formulation first provides an elegant model for the problem under study. Furthermore, it enables solutions to the problem instances beyond the capability of exact methods developed so far. In order to alleviate computational burden, the authors propose MIP-based heuristic approaches which balance solution quality and computing time.

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“…Oulamara et al [20] and Liao and Liao [21] investigated problem of tasks scheduling in a flowshop with two BPMs. They considered the makespan objective and presented heuristic approaches to solve it.…”

Section: Introductionmentioning

confidence: 99%

The openshop batch processing problem with non-identical processing times, using simulated annealing and genetic algorithms approaches

Khormali¹,

Mirzazadeh²,

Faez³

2011

Int J Adv Manuf Technol

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This paper addresses batch processing problem on the multimachine openshop. In the batch processing problem, jobs are categorized into batches and the batches are processed by machines. The processing time of each batch equals the maximum processing time of the batch jobs. The objective is to minimize the makespan. We assume non-identical processing time jobs. We used metaheuristic algorithms, including simulated annealing and genetic algorithms to solve the problem. Several numerical experiments show that for the small size problems, the proposed methods generate the solutions by no deviation or a little deviation from the global optimum. Furthermore, for the large-size problems, the proposed methods generate better solutions in a few times as compared to the commercial optimization software Lingo 8.

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Improved MILP models for two-machine flowshop with batch processing machines

Cited by 27 publications

References 6 publications

Scheduling of printed circuit board (PCB) assembly systems with heterogeneous processors using simulation-based intelligent optimization methods

Scheduling of printed circuit board (PCB) assembly systems with heterogeneous processors using simulation-based intelligent optimization methods

MIP formulations and heuristics for solving parallel batching problems

The openshop batch processing problem with non-identical processing times, using simulated annealing and genetic algorithms approaches

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