scholarly journals Production Planning through Lean Manufacturing and Mixed Integer Linear Programming

2021 ◽  
Vol 21 (1) ◽  
pp. 47-62
Author(s):  
José Israel HERNÁNDEZ VÁZQUEZ ◽  
Salvador HERNÁNDEZ GONZÁLEZ ◽  
José Omar HERNÁNDEZ VÁZQUEZ ◽  
José Alfredo JIMÉNEZ GARCÍA ◽  
María del Rosario BALTAZAR FLORES
Keyword(s):  
Linear Programming ◽  
Production Planning ◽  
Integer Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Lean Manufacturing ◽  
Mixed Integer ◽  
Lead Times ◽  
New Strategy ◽  
The City

Production planning is one of the most important administrative decisions a company can make, as it involves achieving the lead times set by the customers while taking advantage of the resources the organization has. Over time, different strategies using mathematical models have been implemented in production planning, aimed at finding the best solution for optimizing the available resources. In recent years companies throughout the world have successfullly implemented Lean Manufacturing, aimed at improving their production processes and eliminating everything that does not add value to the product. This article exemplifies a new strategy for production planning, using basic concepts from Lean Manufacturing and mixed integer linear programming models by stages. We took a women’s footwear factory in the city of León, Guanajuato, México, as a case study. The results show that it is possible to get planning that optimizes the organization’s resources and shortens the products’ lead times by shrinking inventories, from a Lean Manufacturing perspective.

scholarly journals A Mixed Integer Linear Programming Model for the Optimization of Steel Waste Gases in Cogeneration: A Combined Coke Oven and Converter Gas Case Study

Energies ◽  
2020 ◽  
Vol 13 (15) ◽  
pp. 3781
Author(s):  
Sergio García García ◽  
Vicente Rodríguez Montequín ◽  
Henar Morán Palacios ◽  
Adriano Mones Bayo
Keyword(s):  
Linear Programming ◽  
Integer Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Programming Model ◽  
Coke Oven ◽  
Linear Programming Model ◽  
Mixed Integer ◽  
Integer Linear Programming Model ◽  
Converter Gas

Off-gas is one of the by-products of the steelmaking process. Its potential energy can be transformed into heat and electricity by means of cogeneration. A case study using a coke oven and Linz–Donawitz converter gas is presented. This work addresses the gas allocation problem for a cogeneration system producing steam and electricity. In the studied facility, located in northern Spain, the annual production of the plant requires 95,000 MWh of electrical energy and 525,000 MWh of thermal energy. The installed electrical and thermal power is 20.4 MW and 81 MW, respectively. A mixed integer linear programming model is built to optimize gas allocation, thus maximizing its benefits. This model is applied to a 24-h scenario with real data from the plant, where gas allocation decision-making was performed by the plant operators. Application of the model generated profit in a scenario where there were losses, increasing benefits by 16.9%. A sensitivity analysis is also performed. The proposed model is useful not only from the perspective of daily plant operation but also as a tool to simulate different design scenarios, such as the capacity of gasholders.

scholarly journals Mixed Integer Linear Programming Models to Solve a Real-Life Vehicle Routing Problem with Pickup and Delivery

2021 ◽  
Vol 11 (20) ◽  
pp. 9551
Author(s):  
Ali Louati ◽  
Rahma Lahyani ◽  
Abdulaziz Aldaej ◽  
Racem Mellouli ◽  
Muneer Nusir
Keyword(s):  
Linear Programming ◽  
Vehicle Routing ◽  
Integer Linear Programming ◽  
Vehicle Routing Problem ◽  
Mixed Integer Linear Programming ◽  
Real Life ◽  
Mixed Integer ◽  
Pickup And Delivery ◽  
Routing Problem

This paper presents multiple readings to solve a vehicle routing problem with pickup and delivery (VRPPD) based on a real-life case study. Compared to theoretical problems, real-life ones are more difficult to address due to their richness and complexity. To handle multiple points of view in modeling our problem, we developed three different Mixed Integer Linear Programming (MILP) models, where each model covers particular constraints. The suggested models are designed for a mega poultry company in Tunisia, called CHAHIA. Our mission was to develop a prototype for CHAHIA that helps decision-makers find the best path for simultaneously delivering the company’s products and collecting the empty boxes. Based on data provided by CHAHIA, we conducted computational experiments, which have shown interesting and promising results.

Multi-criteria decision analysis for pharmaceutical supplier selection problem using fuzzyTOPSIS

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Umar Muhammad Modibbo ◽  
Musa Hassan ◽  
Aquil Ahmed ◽  
Irfan Ali
Keyword(s):  
Decision Making ◽  
Linear Programming ◽  
Pharmaceutical Company ◽  
Integer Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Supplier Selection ◽  
Mixed Integer ◽  
Pharmaceutical Companies ◽  
Content Type

PurposeSupplier selection in the supply chain network (SCN) has strategic importance and involves multiple factors. The multi-criteria nature of the problem coupled with environmental uncertainty requires several procedures and considerations. The issue of decision-making in selecting the best among various qualified suppliers remains the major challenge in the pharmaceutical industry. This study investigated the multi-criteria multi-supplier decision-making process and proposed a model for supplier selection problems based on mixed-integer linear programming.Design/methodology/approachThe concept of principal component analysis (PCA) was used to reduce data dimensionality, and the four best criteria have been considered and selected. The result is subjected to decision-makers’ (DMs’) reliability test using the concept of a triangular fuzzy number (TFN). The importance of each supplier to each measure is established using fuzzy technique for order preference by similarity to an ideal solution approach, and the suppliers have ranked accordingly.FindingsThis study proposes a mixed integer linear programming model for supplier selection in a pharmaceutical company. The effectiveness of the proposed model has been demonstrated using a numerical example. The solution shows the model's applicability in making a sound decision in pharmaceutical companies in the space of reality. The model proposed is simple. Readily commercial packages such as LINDO/LINGO and GAMS can solve the model.Research limitations/implicationsThis research contributed to the systematic manner of supplier selection considering DMs’ value judgement under a fuzzy environment and is limited to the case study area. However, interested researchers can apply the study in other related manufacturing industries. However, the criteria have to be revisited to suit that system and might require varying ratings based on the experts' opinions in that field.Practical implicationsThis work suggests more insights practically by considering a realistic and precise investigation based on a real-life case study of pharmaceutical companies with six primary criteria and twenty-four sub-criteria. The study outcome will assist organizations and managers in conducting the best decision objectively by selecting the best suppliers with their various standards and terms among many available contenders in the manufacturing industry.Originality/valueIn this paper, the authors attempted to identify the most critical attributes to be preserved by the top managers (DMs) while selecting suppliers in pharmaceutical companies. The study proposed an MILP model for supplier selection in the pharmaceutical company using fuzzy TOPSIS.

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