scholarly journals Production Scheduling Mathematical Model in Garment Industry

Author(s):  
Nguyen Van Thanh

In this paper, the author introduces about building the support system of production schedule, based on the linear programming model, exploiting effectively Branch and Bound (BnB) algorithms in Lingo software. In addition, the result of the study is the software that supports production schedule based on the C# programming language, friendly interface makes the operator easy to use. After the implementation and final test, the research model is applied to the case of the garment company to support the production schedule, reduces the number of orders delayed, shorten the production time to increase profits for the company.


Author(s):  
Nguyen Van Thanh

In this paper, the author introduces about building the support system of production schedule, based on the linear programming model, exploiting effectively Branch and Bound (BnB) algorithms in Lingo software. In addition, the result of the study is the software that supports production schedule based on the C# programming language, friendly interface makes the operator easy to use. After the implementation and final test, the research model is applied to the case of the garment company to support the production schedule, reduces the number of orders delayed, shorten the production time to increase profits for the company.



Author(s):  
José Manuel Velarde-Cantú ◽  
Mauricio López-Acosta ◽  
Allán Chacara-Montes ◽  
Ernesto Ramírez-Cárdenas

This paper addresses the problem of production scheduling under a practical approach, which seeks to find out what would be the product mix to ensure the company to obtain the most useful, also requires that these combinations of products obtained from quickly and efficiently contributing thus to achieve lower costs associated with production. A specific mathematical model based on integer linear programming applied specifically to the product mix is presented, as well as the results obtained from the practical problem from the use of the model in integer linear programming, the use of the software and considering the own conditions of the problem addressed here.



2018 ◽  
Vol 66 (11) ◽  
pp. 950-963 ◽  
Author(s):  
Egidio Leo ◽  
Sebastian Engell

Abstract For the optimal operation of power-intensive plants, a challenge which is addressed in this work is to simultaneously determine the optimal production schedule and the optimal day-ahead electricity commitment. In order to ensure stability of the power grid, the electricity suppliers impose a daily electricity commitment to large consumers. The consumers have to commit one day in advance to the amount of energy they are going to purchase and use for a horizon of 24 hours (with an hourly discretization) and in case the actual electricity consumption differs significantly from the committed profile, the consumer is obliged to pay penalties. Since the consumers have to commit to the electricity suppliers before the actual electricity demand is known, uncertainty needs to be taken into account. A stochastic mixed-integer linear programming model is developed to consider two critical sources of uncertainty: equipment breakdowns and deviation prices. Equipment breakdowns can reduce the production capacity and make the actual electricity consumption deviate from the day-ahead electricity commitment. The application of the proposed approach to a continuous power-intensive plant shows the benefit gained from the solution of the stochastic model instead of the deterministic counterpart in terms of reduction of the cost of the energy.





2012 ◽  
Vol 548 ◽  
pp. 767-771 ◽  
Author(s):  
C. Vanlisuta ◽  
Suksan Prombanpong

The objective of this paper is to determine the number and species of trees to be planted in order to maximize a profit through an integer linear programming model. The mathematical model is developed in terms of the profit function. This objective function is therefore, a difference between carbon credit revenue and costs of plantation. The economical plants are only considered in the model. Consequently, fourteen different tree species are to be investigated. The objective function is subjected to several constraints i.e. planting area, carbon sequestration and so on. The planting envelope of each tree is assigned 4 by 4 meters. In this paper, the Eastern part of Thailand is considered the case study. It is found that three kinds of plants, Copper pod, Cananga, and Bullet wood are suitable for planting. A number of trees to be planted in 1600 square meter are twenty, thirty, and fifty plants respectively. The profit earned is of 12,112 $ per year in the next fifth year.



2020 ◽  
Vol 26 (6) ◽  
pp. 579-589
Author(s):  
Piotr Jaskowski ◽  
Slawomir Biruk

The highest degree of construction works harmonization can be achieved when planning a repetitive project with processes replicated many times in work zones of identical size. In practice, structural considerations affect the way of dividing the object under construction into zones differing in terms of scope and quantity of works. Due to this fact, individual processes are being allotted to different non-identical zones. Most methods intended for scheduling repetitive processes were developed with the assumption that the work zones are identical and that a particular process cannot be concurrently conducted. To address this gap, the authors put forward a mathematical model of the problem of scheduling of repetitive processes that are repeated in different work zones with the following assumption: several crews of the same type are available, thus particular process can run simultaneously in different locations. The aim of optimization is minimizing the idle time of all crews under the constraint of not exceeding the contractual project duration. The proposed mixed binary linear programming model can be solved using software available in the market or developed into a dedicated system to support decisions. To illustrate the benefits of the model, an example of scheduling interior finishing works was provided.



2021 ◽  
Vol 15 ◽  
pp. 8-13
Author(s):  
Mohamed K. Omar ◽  
Muzalna Mohd-Jusoh ◽  
Mohd Omar

This paper considers the hierarchical production planning (HPP) concept to solve a production planning problem in the process industry in a fuzzy environment. The adopted fuzzy HPP consists of two levels in which a fuzzy aggregate production planning (FAPP) model is developed in the first level, and then a fuzzy disaggregate production planning (FDPP) model is developed at the second level. The FAPP was reported by Omar et al. [1] and therefore, this research paper discusses the FDPP model. We formulated the disaggregate model as a fuzzy mixed-integer linear programming model that aims to develop a master production schedule in which numbers of optimal batches are developed in presence of setup time. In addition, we evaluate the performance of the FMILP by comparing its results with a previously reported approach. The findings indicate that significant cost savings were achieved by adopting the fuzzy mathematical programming approach.



2020 ◽  
Vol 2 (2) ◽  
pp. 13
Author(s):  
Imam Ekowicaksono ◽  
I Wayan Wiprayoga Wisesa

At the beginning of each semester, the faculty member will determine the teaching load for each lecturer. Teaching load assigned for each lecturer is carried out by considering the lecturers' courses and scientific groups. In addition, the assignment method for teaching load consider the balance of the average teaching load. This study investigate the teaching load assignment problem considering the balance of the teaching load for each lecturer. The linear programming model is used to model the teaching load of lecturers. This teaching load model was applied at the Informatics Program, Institut Teknologi Sumatera for the even semester. The model yields a minimum total deviation of the average teaching load of lecturers is 8.05 credits, calculated using the branch and bound algorithm with 7,258,538 iterations.



Author(s):  
Mar Vazquez-Noguerol ◽  
Jose A. Comesaña-Benavides ◽  
Sara Riveiro-Sanroman ◽  
J. Carlos Prado-Prado

AbstractThe use of the online channel has greatly increased the logistics costs of supermarket chains. Even the difficulty of managing order picking and delivery processes has increased due to the short delivery times and the preservation of perishable products. Against that backdrop, the proposed approach presents a mathematical model for planning the e-fulfillment activities with the objective of ensuring maximum efficiency. The linear programming model has been designed for e-grocers that prepare their online orders at central warehouses. The mathematical model determines both the time windows during which picking and transport should take place and the assignment of trucks to delivery routes. The allocation of online orders is performed taking into account the conservation requirement of each type of product and the availability of means. Considering this planning tool, managers can improve the decision-making process guaranteeing the quality of service while reducing the e-fulfillment cost for joint picking and delivery point of view. Motivated by a cooperation with a supermarket chain, results bring great insight based on the simulation of different logistics alternatives. Companies and researchers can compare the strategy of leveling the workload and the strategy of reducing the number of means, a common alternative in logistics outsourced to third parties. In addition, the different scenarios developed make it possible to determine the substantial savings achieved by modifying the delivery services and advancing the order preparation. As a result, managerial insights are identified highlighting the importance of efficient order planning to improve the profitability of online sales.



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