scholarly journals Production Scheduling Mathematical Model in Garment Industry

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Nguyen Van Thanh
Keyword(s):  
Mathematical Model ◽  
Linear Programming ◽  
Branch And Bound ◽  
Production Scheduling ◽  
Programming Model ◽  
Research Model ◽  
Production Schedule ◽  
Final Test ◽  
C Programming Language ◽  
C Programming

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.

Production Scheduling Mathematical Model in Garment Industry

2021 ◽  
Vol 10 (2) ◽  
pp. 60-67
Author(s):  
Nguyen Van Thanh
Keyword(s):  
Mathematical Model ◽  
Linear Programming ◽  
Branch And Bound ◽  
Production Scheduling ◽  
Programming Model ◽  
Research Model ◽  
Production Schedule ◽  
Final Test ◽  
C Programming Language ◽  
C Programming

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.

scholarly journals Production optimization by using integer linear programming under a practical approach

2020 ◽  
pp. 1-7
Author(s):  
José Manuel Velarde-Cantú ◽  
Mauricio López-Acosta ◽  
Allán Chacara-Montes ◽  
Ernesto Ramírez-Cárdenas
Keyword(s):  
Mathematical Model ◽  
Linear Programming ◽  
Integer Linear Programming ◽  
Production Scheduling ◽  
Practical Problem ◽  
Production Optimization ◽  
Practical Approach ◽  
Product Mix ◽  
Model Based

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.

scholarly journals Integrated day-ahead energy procurement and production scheduling

2018 ◽  
Vol 66 (11) ◽  
pp. 950-963 ◽  
Author(s):  
Egidio Leo ◽  
Sebastian Engell
Keyword(s):  
Production Scheduling ◽  
Programming Model ◽  
Production Capacity ◽  
Electricity Consumption ◽  
Optimal Operation ◽  
Mixed Integer ◽  
Production Schedule ◽  
Sources Of Uncertainty ◽  
Continuous Power ◽  
The Cost

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.

An Integer Programming Approach to Optimize the Plantation in Order to Reduce Global Warming

2012 ◽  
Vol 548 ◽  
pp. 767-771 ◽  
Author(s):  
C. Vanlisuta ◽  
Suksan Prombanpong
Keyword(s):  
Mathematical Model ◽  
Linear Programming ◽  
Objective Function ◽  
Programming Model ◽  
Programming Approach ◽  
Profit Function ◽  
Carbon Credit ◽  
Integer Linear Programming Model ◽  
The Mathematical Model

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.

scholarly journals SCHEDULING OF REPETITIVE CONSTRUCTION PROCESSES WITH CONCURRENT WORK OF SIMILARLY SPECIALIZED CREWS

2020 ◽  
Vol 26 (6) ◽  
pp. 579-589
Author(s):  
Piotr Jaskowski ◽  
Slawomir Biruk
Keyword(s):  
Mathematical Model ◽  
Linear Programming ◽  
Programming Model ◽  
Idle Time ◽  
Work Zones ◽  
Repetitive Processes ◽  
Project Duration ◽  
Binary Linear Programming ◽  
Under Construction ◽  
Construction Works

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.

scholarly journals Developing a Master Production Schedule Using Fuzzy Mixed Integer Linear Programming

2021 ◽  
Vol 15 ◽  
pp. 8-13
Author(s):  
Mohamed K. Omar ◽  
Muzalna Mohd-Jusoh ◽  
Mohd Omar
Keyword(s):  
Linear Programming ◽  
Production Planning ◽  
Integer Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Programming Model ◽  
Mixed Integer ◽  
Programming Approach ◽  
Planning Problem ◽  
Production Schedule ◽  
Master Production Schedule

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.

Determining Production Schedule with Resource Constraints Using Drum-Buffer-Rope (DBR) Approach

2012 ◽  
Vol 488-489 ◽  
pp. 1130-1133 ◽  
Author(s):  
Ping Yu Chang
Keyword(s):  
Mathematical Model ◽  
Production Scheduling ◽  
Feasible Solution ◽  
Resource Constraints ◽  
Optimal Solution ◽  
Hard Problem ◽  
Improve Quality ◽  
Production Schedule ◽  
Np Hard Problem ◽  
Wafer Manufacturing

In wafer plants, product will be manufactured through same process with different setups and specifications. This special manufacturing process is described as re-entrant flows. In photo process of wafer manufacturing, products is also restricted to be processed through same machine in each reentrance to improve quality. This phenomenon will cause scheduling in photo process being complicated and is proved to be a NP-hard problem. This research develops a mathematical model for photo process to minimize the makespan. A feasible solution is achieved using DBR (drum-buffer-rope) method. The results are compared to the optimal solution that is achieved using branch and bound algorithm. Our results show that DBR based method achieves a near optimal solution in shorter time. The results also indicate that DBR method can be useful in production scheduling with resource constraints.

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