An integer linear programming model to support customer-driven material planning in synchronised, multi-tier supply chains

Lyons, Andrew C.; Hernández, Jorge E.; Mula, Josefa

doi:10.1080/00207543.2013.878055

Cited by 18 publications

(7 citation statements)

References 33 publications

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“…en, the first-tier supplier obtains its demand by using a simple bill-of-materials parts explosion, given the OEM demand plan. e second-tier supplier estimates the component requirements from the final requirements in a frozen sequence transferred by the first-tier supplier, and the demand plan is generated [18]. en, the second-tier supplier proceeds to compute the LSSP model with the aim of (i) assigning molds to machines; (ii) scheduling the processing molds in machines during each planning time period; and (iii) calculating the optimal lot size of products.…”

Section: Problem Descriptionmentioning

confidence: 99%

“…Constraint (31) indicates the binary nature of the setup S iljt and setup amount SA iljt variables. Finally, the MILP model for lot sizing and scheduling on parallel flexible injection machines with setup common operators is also subject to constraints (6), ( 8), (13a), (13b), ( 14)-( 16), (18), and (19). e performance of the proposed model was evaluated on a set of instances that reflect different characteristics of the real-world case of the automotive components industry under study.…”

Section: Bound and Nature Variablesmentioning

confidence: 99%

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A Novel MILP Model for the Production, Lot Sizing, and Scheduling of Automotive Plastic Components on Parallel Flexible Injection Machines with Setup Common Operators

2021

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In this article, a mixed integer linear program (MILP) model is proposed for the production, lot sizing, and scheduling of automotive plastic components to minimize the setup, inventory, stockout, and backorder costs, by taking into account injection molds as the main index to schedule on parallel flexible injection machines. The proposed MILP considers the minimum and maximum inventory capacities and penalizes stockout. A relevant characteristic of the modeled problem is the dependence between mold setups to produce plastic components. The lot sizing and scheduling problem solution results in the assignment of molds to machines during a specific time period and in the calculation of the number of components to be produced, which is often called lot size, following a sequence-dependent setup time. Depending on the machine on which the mold is setup, the number of units to be produced will be distinct because machines differ from one another. The stock coverage, defined in demand days, is also included in the MILP to avoid backorders, which is highly penalized in the automotive supply chain. Added to this, the proposed model is extended by considering setup common operators to respond to and fulfill the constraints that appear in automotive plastic enterprises. In this regard, the MILP presented solves a lot-sizing and scheduling problem, emerged in a second-tier supplier of a real automotive supply chain. Finally, this article validates the MILP by performing experiments with different sized instances, including small, medium, and large. The large-sized dataset is characterized by replicating the amount of data used in the real enterprise, which is the object of this study. The goodness of the model is evaluated with the computational time and the deviation of the obtained results as regards to the optimal solution.

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Section: Problem Descriptionmentioning

confidence: 99%

Section: Bound and Nature Variablesmentioning

confidence: 99%

A Novel MILP Model for the Production, Lot Sizing, and Scheduling of Automotive Plastic Components on Parallel Flexible Injection Machines with Setup Common Operators

2021

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“…Similarly, the supply chains in transport framework also have been broadly discussed. For instance, Mula et al [1] presented a review of mathematical programming models for supply chain production and transport planning. Xie et al [2] developed a multistage, mixed inter programming model to fully integrate multimodal transport into the cellulosic biofuel supply chain design under feedstock seasonality.…”

Section: Introductionmentioning

confidence: 99%

Optimal Flow Distribution of Military Supply Transportation Based on Network Analysis and Entropy Measurement

Zhou

Chen

Ding

2018

Entropy

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One important element of military supply transportation is concealment, especially during war preparations and warfare periods. By introducing entropy to calculate the transportation concealment degree, we investigate the issue about concealed military supply transportation on the whole road network and propose an optimal flow distribution model. This model's objective function is to maximize the concealment of military supply transportation. After analyzing the road network, classifying different nodes, summarizing the constraint conditions based on the properties and assumptions in the transportation process, and combining the general parameter limits, the optimal flow distribution model is further transformed into a calculable non-linear programming model. Thus, based on this non-linear programming model, we can obtain the optimal distribution scheme of military supply transportation from the perspectives of network analysis and concealment measurement. Lastly, an example of military supply transportation in Jiangsu province, China is illustrated to prove the feasibility of the proposed model. The managerial implication is that by utilizing the proposed flow distribution model, military supplies can be efficiently transported to the required destinations based on maximizing the concealment degree. Not only this model can be utilized in the real military supply transportation, it can be also applied in other transportation fields which require time efficiency and concealment.

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“…Developed mathematical models enable optimization of all supply chain resources, including subcontractors realizing delivery orders in a multi-level structure [23,24]. High applicability of ILP problem is furthermore confirmed by the results of a study devoted to scheduling in a river transportation system model [25]. Moreover, ILP problem is also used in the development of sequential algorithms carrying out packaging optimization tasks [26].…”

Section: Introductionmentioning

confidence: 88%

A new interactive approach for solving fully fuzzy mixed integer linear programming

2020

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In this paper, a novel method to solve Fully Fuzzy Mixed Integer Linear Programming (FFMILP) problems is presented. Our method is based on the definition of membership function and a fuzzy interactive technique for solving the classical multiobjective programming. It is worthwhile to note that this is the first time that the fully fuzzy mixed integer linear programming problem is discussed and a solving method is presented. To illustrate the steps of the proposed method, some numerical examples are solved and the results are compared with other methods in the literature. Computational results present the application of the method.

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An integer linear programming model to support customer-driven material planning in synchronised, multi-tier supply chains

Cited by 18 publications

References 33 publications

A Novel MILP Model for the Production, Lot Sizing, and Scheduling of Automotive Plastic Components on Parallel Flexible Injection Machines with Setup Common Operators

A Novel MILP Model for the Production, Lot Sizing, and Scheduling of Automotive Plastic Components on Parallel Flexible Injection Machines with Setup Common Operators

Optimal Flow Distribution of Military Supply Transportation Based on Network Analysis and Entropy Measurement

A new interactive approach for solving fully fuzzy mixed integer linear programming

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