Production Planning Optimization in F Company: A Scheduling Theory Case Study

2013 ◽  
Vol 655-657 ◽  
pp. 1646-1649 ◽  
Author(s):  
Chi Zhang ◽  
Zhen He ◽  
Yuan Peng Ruan
Keyword(s):  
Linear Programming ◽  
Production Planning ◽  
Optimization Problem ◽  
Assembly Line ◽  
Scheduling Theory ◽  
Scheduling Model ◽  
Planning Optimization ◽  
Optimization Methodology ◽  
Optimum Production

Scheduling is an effective optimization methodology which has been widely used for production planning. This paper presents a scheduling model to optimize the output of an assembly line in F Semiconductor Company in Tianjin, China. The authors formulate the optimization problem as linear programming. The model and its implementation are described in detail in this article. The optimum production allocations have been founded by the scheduling model and the output has been increased.

scholarly journals Fertilizer Production Planning Optimization Using Particle Swarm Optimization-Genetic Algorithm

2019 ◽  
Vol 5 (2) ◽  
pp. 120
Author(s):  
Dinita Rahmalia ◽  
Teguh Herlambang ◽  
Thomy Eko Saputro
Keyword(s):  
Genetic Algorithm ◽  
Linear Programming ◽  
Particle Swarm Optimization ◽  
Constrained Optimization ◽  
Production Planning ◽  
Particle Swarm ◽  
Optimal Solution ◽  
Swarm Optimization ◽  
Mutation Probability ◽  
Planning Optimization

Background: The applications of constrained optimization have been developed in many problems. One of them is production planning. Production planning is the important part for controlling the cost spent by the company.Objective: This research identifies about production planning optimization and algorithm to solve it in approaching. Production planning model is linear programming model with constraints : production, worker, and inventory.Methods: In this paper, we use heurisitic Particle Swarm Optimization-Genetic Algorithm (PSOGA) for solving production planning optimization. PSOGA is the algorithm combining Particle Swarm Optimization (PSO) and mutation operator of Genetic Algorithm (GA) to improve optimal solution resulted by PSO. Three simulations using three different mutation probabilies : 0, 0.01 and 0.7 are applied to PSOGA. Futhermore, some mutation probabilities in PSOGA will be simulated and percent of improvement will be computed.Results: From the simulations, PSOGA can improve optimal solution of PSO and the position of improvement is also determined by mutation probability. The small mutation probability gives smaller chance to the particle to explore and form new solution so that the position of improvement of small mutation probability is in middle of iteration. The large mutation probability gives larger chance to the particle to explore and form new solution so that the position of improvement of large mutation probability is in early of iteration.Conclusion: Overall, the simulations show that PSOGA can improve optimal solution resulted by PSO and therefore it can give optimal cost spent by the company for the  planning.Keywords: Constrained Optimization, Genetic Algorithm, Linear Programming, Particle Swarm Optimization, Production Planning

scholarly journals OPTIMIZATION OF PRODUCTION ON SMALL BUSINESS TERRY CHIPS IN THE NYANGLAN KAJA VILLAGE, TEMBUKU DISTRICT, BANGLI REGENCY

2018 ◽  
Vol 7 (11) ◽  
pp. 6011
Author(s):  
Ni Putu Krisnadewi ◽  
Putu Yudi Setiawan
Keyword(s):  
Linear Programming ◽  
Small Business ◽  
Maximum Profit ◽  
Net Profit ◽  
Limited Company ◽  
Break Even Point ◽  
Corporate Resources ◽  
Programming Analysis ◽  
Optimum Production

Optimizing the production can be obtained by regulating the use of limited company resources. The purpose of this study is to know the optimization of corporate resources to generate maximum profit. The case study was conducted on Terry Kripik Small Business in Nyanglan Kaja Village, Tembuku Subdistrict, Bangli District. Based on the results of linear programming analysis with the help of POM-QM software, optimum production is 9 sacks of Ladrang Chips, 71 sacks of Chicken Chips, 46 sacks of Spinach Chips and 74 sacks of Limo Stick Leaf Chips. BEP value is Rp 30.708.228,00 or equal to 72 sacks. The projection of net profit if production is on demand is Rp 8,293,323.00 while net profit if produced according to the optimal product combination is Rp 11,718,143.00. Companies are encouraged to combine linear programming analysis, break even point, and cost analysis as input for management in making decisions related to optimization. Keywords: optimization of production, maximum profit, terry chips, and linear programming

scholarly journals Polymorphic Uncertain Linear Programming for Generalized Production Planning Problems

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Xinbo Zhang ◽  
Feng Zhang ◽  
Xiaohong Chen ◽  
Zhong Wan
Keyword(s):  
Linear Programming ◽  
Production Planning ◽  
Raw Material ◽  
Interval Numbers ◽  
Robust Solution ◽  
Deterministic Equivalent ◽  
Uncertain Optimization ◽  
Planning Problems ◽  
Fuzzy Interval

A polymorphic uncertain linear programming (PULP) model is constructed to formulate a class of generalized production planning problems. In accordance with the practical environment, some factors such as the consumption of raw material, the limitation of resource and the demand of product are incorporated into the model as parameters of interval and fuzzy subsets, respectively. Based on the theory of fuzzy interval program and the modified possibility degree for the order of interval numbers, a deterministic equivalent formulation for this model is derived such that a robust solution for the uncertain optimization problem is obtained. Case study indicates that the constructed model and the proposed solution are useful to search for an optimal production plan for the polymorphic uncertain generalized production planning problems.

Linear Programming Applied to Production Planning -- A Case Study

OR ◽  
1964 ◽  
Vol 15 (4) ◽  
pp. 293
Author(s):  
W. G. Jones ◽  
C. M. Rope
Keyword(s):  
Linear Programming ◽  
Production Planning

scholarly journals “Case Study: Application for optimizing the product mix problem of linear programming in the Apparel Industry”

2021 ◽  
Vol 23 (07) ◽  
pp. 1091-1098
Author(s):  
Varsha Rathi ◽  
◽  
Sangeeta Gupta ◽  
Sweta Srivastav ◽  
◽  
...  
Keyword(s):  
Linear Programming ◽  
Optimization Problem ◽  
Apparel Industry ◽  
Management Decision ◽  
Effective Management ◽  
Product Mix ◽  
Management Decision Making ◽  
Labor Resources ◽  
Study Application

The industry has made effective management decision-making techniques possible through surveys and the efficient use of sources and assets. Linear programming can be used for the optimization problem of product mix. We have to understand the concept behind the optimization problem of product mix is important to get success in the industry for meeting customer needs. The manufacturing profit depends on the proper distribution of product material and usage of available production time material and labor resources. The findings of the study show that the profit of the company and the demand for the product.

scholarly journals The Optimization Problem of Product Mix and Linear Programming Applications: Case Study in the Apparel Industry

2017 ◽  
Vol 2 (2) ◽  
Author(s):  
Gera Workie Woubante
Keyword(s):  
Decision Making ◽  
Linear Programming ◽  
Inventory Management ◽  
Industrial Development ◽  
Optimization Problem ◽  
Management Decision ◽  
Product Mix ◽  
Use Of Resources ◽  
Customer Orders

Industrial development strategy is characterized by the efficient use of resources at every production stage. The analysis and efficient utilization of resources are made sustainable by effective management decision making techniques employed in the industry. A quantitative decision making tool called linear programming can be used for the optimization problem of product mix. Understanding the concept behind the optimization problem of product mix is essential to the success of the industry for meeting customer needs, determining its image, focusing on its core business, and inventory management. Apparel manufacturing firms profit mainly depends on the proper allocation and usage of available production time, material, and labor resources. This paper considers an apparel industrial unit in Ethiopia as a case study. The monthly held resources, product volume, and amount of resources used to produce each unit of product and profit per unit for each product have been collected from the company. The data gathered was used to estimate the parameters of the linear programming model. The model was solved using LINGO 16.0 software. The findings of the study show that the profit of the company can be improved by 59.84%, that is, the total profit of Birr 465,456 per month can be increased to Birr 777,877.3 per month by applying linear programming models if customer orders have to be satisfied. The profit of the company can be improved by 7.22% if the linear programming formulation does not need to consider customer orders.

Sign in / Sign up

Export Citation Format

Share Document