Simulation framework for determining the order and size of the product batches in the flow shop: A case study

Ištoković, David; Perinić, Mladen; Doboviček, Sandro; Bazina, Tomislav

doi:10.14743/apem2019.2.319

Cited by 11 publications

(13 citation statements)

References 26 publications

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“…(14). All batch sizes of a particular product will be equal except one, which will amount to as much as the difference to the defined total quantity of products [24]. This single batch can be produced as a residue in the form of the last batch BS j,last , or in the form of the first batch BS j,first , which leads to two optimization cases.…”

Section: Methodology and Problem Assumptionsmentioning

confidence: 99%

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Determining the Minimum Waiting Times in a Hybrid Flow Shop Using Simulation-Optimization Approach

2021

Teh. vjesn.

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Planning the order and size of batches is an extremely complex task especially if these tasks are related to production companies in a real environment. This research deals with the problem of determining the entry order and size of product batches in order to optimize inter-operational waits, in the form of waiting in queues for processing and waiting due to the setting-up of the workplace. In real environment, these waits represent a large share of the time spent in the production of a unit of product in a hybrid flow shop. This problem is almost impossible to be solved with analytical models because they may require many simplifying assumptions. Therefore, a simulationoptimization approach is used to solve this problem. Discrete event simulation allows greater flexibility in the representation of the real production system, while the integrated optimization tool, a genetic algorithm, serves to find the optimal solution relatively quickly. To ensure simpler production management, batch size is defined as a fixed value with the exception of a different first or last batch which represents the difference to the required production volume. Therefore, two optimization cases are presented in the paper. Although both cases show improvements, the case when a different batch is the first batch shows better results. In that case, the share of setup time in the total production time of the product unit was reduced from 4% to 3%, and the share of waiting time in the queue for processing was reduced from 76% to 32%.

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Section: Methodology and Problem Assumptionsmentioning

confidence: 99%

“…The order of activities in HFS will be determined using the probability of entering a batch of products. However, unlike the author [24], the probability of entering a particular batch is determined as a direct value in the form of a percentage, Eq. (15) and Eq.…”

Section: Methodology and Problem Assumptionsmentioning

confidence: 99%

Determining the Minimum Waiting Times in a Hybrid Flow Shop Using Simulation-Optimization Approach

2021

Teh. vjesn.

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“…To date, some methods to solve the scheduling problem with resource constraints have been developed depending on the problem statement, restrictions, and objective function. These are scheduling theory and network methods [1][2][3][4][5], simulation and multi-agent modelling methods [6,7], heuristic methods [8,9], and methods based on the application of commercially available solvers [10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

“…According to the machine environment, scheduling problems can be divided into the main following types with the type notation in brackets [15]: identical parallel machines (Pm) where work can be performed at any of the machines [1][2][3][4][5]8,9,12,14]; Job shop (Jm) where each work has to be processed on each of the machines and all works have different routes [6,7,11,13]; Open shop (Om) where each work has to be processed on each of the machines and some of this processing time may be zero [10].…”

Section: Introductionmentioning

confidence: 99%

An Imitation and Heuristic Method for Scheduling with Subcontracted Resources

2021

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A scheduling problem with subcontracted resources is widely spread and is associated with the distribution of limited renewable and non-renewable resources, both own and subcontracted ones based on the work’s due dates and the earliest start time. Scheduling’s goal is to reduce the cost of the subcontracted resources. In the paper, application of a few scheduling methods based on scheduling theory and the optimization algorithm is considered; limitations of these methods’ application are highlighted. It is shown that the use of simulation modeling with heuristic rules for allocation of the renewable resources makes it possible to overcome the identified limitations. A new imitation and heuristic method for solving the assigned scheduling problem is proposed. The comparison of the new method with existing ones in terms of the quality of the found solution and performance of the methods is carried out. A case study is presented that allowed a four-fold reduction of the overall subcontracted resources cost in a real project portfolio.

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“…are common examples. Scheduling has also a wide range of application in manufacturing from supply chain activities to production operations [3,4]. From manufacturing point of view, scheduling seeks for an optimum execution sequence of given jobs on a set of machines to optimize defined objective(s) such as makespan, flow time, tardiness, idle time, etc.…”

Section: Introductionmentioning

confidence: 99%

An Integrated Solution Approach for Flow Shop Scheduling

Karacan

Şenvar

et al. 2021

Teh. vjesn.

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This study seeks to integrate Random Key Genetic Algorithm (RKGA) and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) to compute makespan and solve the Flow Shop Scheduling Problem (FSSP). FSSP is considered as a Multi Criteria Decision Making Problem (MCDM) by setting machines as criteria and jobs as alternatives. RKGA is employed to determine the best weights for the criteria that directly affect the robustness of the solution. The proposed methodology is presented with illustrative example and applied to benchmark problems. The solutions are compared to well-known construction heuristics. The proposed methodology provides the best or reasonable solutions in acceptable computational times.

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Simulation framework for determining the order and size of the product batches in the flow shop: A case study

Cited by 11 publications

References 26 publications

Determining the Minimum Waiting Times in a Hybrid Flow Shop Using Simulation-Optimization Approach

Determining the Minimum Waiting Times in a Hybrid Flow Shop Using Simulation-Optimization Approach

An Imitation and Heuristic Method for Scheduling with Subcontracted Resources

An Integrated Solution Approach for Flow Shop Scheduling

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