scholarly journals A Four-Type Decision-Variable MINLP Model for a Supply Chain Network Design

2010 ◽  
Vol 2010 ◽  
pp. 1-16 ◽  
Author(s):  
M. M. Monteiro ◽  
J. E. Leal ◽  
F. M. P. Raupp
Keyword(s):  
Supply Chain ◽  
Programming Model ◽  
Planning Horizon ◽  
Mixed Integer ◽  
Decision Variable ◽  
Abc Classification ◽  
Computational Implementation ◽  
Minlp Model ◽  
Nonlinear Programming Model ◽  
Outer Approximation Algorithm

We propose a mixed integer nonlinear programming model for the design of a one-period planning horizon supply chain with integrated and flexible decisions on location of plants and of warehouses, on levels of production and of inventory, and on transportation models, considering stochastic demand and the ABC classification for finished goods, which is an NP-hard industrial engineering optimization problem. Furthermore, computational implementation of the proposed model is presented through the direct application of the outer approximation algorithm on some randomly generated supply chain data.

scholarly journals Production Planning Problem of a Two-Level Supply Chain with Production-Time-Dependent Products

2021 ◽  
Vol 11 (20) ◽  
pp. 9687
Author(s):  
Jun-Hee Han ◽  
Ju-Yong Lee ◽  
Bongjoo Jeong
Keyword(s):  
Supply Chain ◽  
Production Planning ◽  
Programming Model ◽  
Planning Horizon ◽  
Mixed Integer ◽  
Planning Problem ◽  
Manufacturing Plant ◽  
Production Lines ◽  
Multiple Production ◽  
Production Planning Problem

This study considers a production planning problem with a two-level supply chain consisting of multiple suppliers and a manufacturing plant. Each supplier that consists of multiple production lines can produce several types of semi-finished products, and the manufacturing plant produces the finished products using the semi-finished products from the suppliers to meet dynamic demands. In the suppliers, different types of semi-finished products can be produced in the same batch, and products in the same batch can only be started simultaneously (at the same time) even if they complete at different times. The purpose of this study is to determine the selection of suppliers and their production lines for the production of semi-finished products for each period of a given planning horizon, and the objective is to minimize total costs associated with the supply chain during the whole planning horizon. To solve this problem, we suggest a mixed integer programming model and a heuristic algorithm. To verify performance of the algorithm, a series of tests are conducted on a number of instances, and the results are presented.

scholarly journals A hybrid NSGA-II algorithm for the closed-loop supply chain network design in e-commerce  

2021 ◽  
Author(s):  
Shayan Shafiee Moghadam ◽  
Amir Aghsami ◽  
Masoud Rabbani
Keyword(s):  
Supply Chain ◽  
Closed Loop ◽  
Programming Model ◽  
Mixed Integer ◽  
Modern World ◽  
Supply Chain Network ◽  
Nsga Ii ◽  
Closed Loop Supply Chain ◽  
Proposed Model ◽  
Nonlinear Programming Model

Designing the supply chain network is one of the significant areas in e-commerce business management. This concept plays a crucial role in e-commerce systems. For example, location-inventory-pricing-routing of an e-commerce supply chain is considered a crucial issue in this field. This field established many severe challenges in the modern world, like maintaining the supply chain for returned items, preserving customers' trust and satisfaction, and developing an applicable supply chain with cost considerations. The research proposes a multi-objective mixed integer nonlinear programming model to design a closed-loop supply chain network based on the e-commerce context. The proposed model incorporates two objectives that optimize the business's total profits and the customers' satisfaction. Then, numerous numerical examples are generated and solved using the epsilon constraint method in GAMS optimization software. The validation of the given model has been tested for the large problems via a hybrid two-level non-dominated sort genetic algorithm. Finally, some sensitivity analysis has been performed to provide some managerial insights.

scholarly journals MINLP Model for Operational Optimization of LNG Terminals

Processes ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 599
Author(s):  
Zhencheng Ye ◽  
Xiaoyan Mo ◽  
Liang Zhao
Keyword(s):  
Energy Consumption ◽  
Natural Gas ◽  
Fossil Fuels ◽  
Programming Model ◽  
Mixed Integer ◽  
Integer Variables ◽  
Operational Optimization ◽  
Minlp Model ◽  
Different Seasons ◽  
Nonlinear Programming Model

Liquefied natural gas (LNG) is a clear and promising fossil fuel which emits less greenhouse gas (GHG) and has almost no environmentally damaging sulfur dioxide compared with other fossil fuels. An LNG import terminal is a facility that regasifies LNG into natural gas, which is supplied to industrial and residential users. Modeling and optimization of the LNG terminals may reduce energy consumption and GHG emission. A mixed-integer nonlinear programming model of the LNG terminal is developed to minimize the energy consumption, where the numbers of boil-off gas (BOG) compressors and low-pressure (LP) pumps are considered as integer variables. A case study from an actual LNG terminal is carried out to verify the practicality of the proposed method. Results show that the proposed approach can decrease the operating energy consumption from 9.15% to 26.1% for different seasons.

scholarly journals A mixed integer nonlinear multiperiod model for supply chain management of a company in the retail sector

2021 ◽  
Author(s):  
Eliana Costa Oliveira da Costa e Silva ◽  
Ana Teixeira ◽  
Cristina Lopes
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Programming Model ◽  
Business Environment ◽  
Mixed Integer ◽  
Retail Sector ◽  
Food Supply Chains ◽  
Nonlinear Programming Model ◽  
Almost All ◽  
Retail Company

The fluctuations in the business environment and seasonal variations characteristic of food supply chains contribute greatly to the increasing complexity of the entire Supply Chain planning. In the present paper, quantitative models are applied to support the decision-making purchasing management department of a retail company. Specifically, a multiperiod mathematical model was developed with the aim of optimizing decision-making of the purchasing managers. The developed model consists of a multiperiod Mixed Integer Nonlinear Programming model, with the objective to minimize the ratio between how much is costing the company to move the products along the Supply Chain and the products' costs. It is discussed how to order the product, what is the most advantageous storage mode and whether it is preferable to order once or twice a week. Real instances, provided by a Portuguese retail company, regarding the demand for one year are tested for two scenarii, which are used currently by the company. The results show that the proposed model can reduce, on both scenarios, the ratio between operational costs and merchandise costs, for almost all products, and therefore it can be an important tool for supporting decision-making of the purchasing manager.

scholarly journals Context-aware heatstroke relief station placement and route optimization for large outdoor events

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Yan Wu ◽  
Tianqi Xia ◽  
Adam Jatowt ◽  
Haoran Zhang ◽  
Xiao Feng ◽  
...  
Keyword(s):  
Physical Environment ◽  
Emergency Service ◽  
Programming Model ◽  
Heterogeneous Data ◽  
Route Optimization ◽  
Mixed Integer ◽  
Context Aware ◽  
Outdoor Activities ◽  
Integer Nonlinear Programming ◽  
Nonlinear Programming Model

Abstract Background Heatstroke is becoming an increasingly serious threat to outdoor activities, especially, at the time of large events organized during summer, including the Olympic Games or various types of happenings in amusement parks like Disneyland or other popular venues. The risk of heatstroke is naturally affected by a high temperature, but it is also dependent on various other contextual factors such as the presence of shaded areas along traveling routes or the distribution of relief stations. The purpose of the study is to develop a method to reduce the heatstroke risk of pedestrians for large outdoor events by optimizing relief station placement, volume scheduling and route. Results Our experiments conducted on the planned site of the Tokyo Olympics and simulated during the two weeks of the Olympics schedule indicate that planning routes and setting relief stations with our proposed optimization model could effectively reduce heatstroke risk. Besides, the results show that supply volume scheduling optimization can further reduce the risk of heatstroke. The route with the shortest length may not be the route with the least risk, relief station and physical environment need to be considered and the proposed method can balance these factors. Conclusions This study proposed a novel emergency service problem that can be applied in large outdoor event scenarios with multiple walking flows. To solve the problem, an effective method is developed and evaluates the heatstroke risk in outdoor space by utilizing context-aware indicators which are determined by large and heterogeneous data including facilities, road networks and street view images. We propose a Mixed Integer Nonlinear Programming model for optimizing routes of pedestrians, determining the location of relief stations and the supply volume in each relief station. The proposed method can help organizers better prepare for the event and pedestrians participate in the event more safely.

scholarly journals Local Blood Supply Chain Optimization: A Case Study

2020 ◽  
Vol 18 (4) ◽  
Author(s):  
Reza Babazadeh ◽  
Ali Sabbaghnia ◽  
Fatemeh Shafipour
Keyword(s):  
Supply Chain ◽  
Blood Supply ◽  
Blood Donation ◽  
Programming Model ◽  
Human Life ◽  
Mixed Integer ◽  
Model Parameters ◽  
Supply Chain Optimization ◽  
Blood Supply Chain ◽  
Proposed Model

: Blood and its products play an undeniable role in human life. In recent years, although both academics and practitioners have investigated blood-related problems, further enhancement is still warranted. In this study, a mixed-integer linear programming model was proposed for local blood supply chain management. A supply network, including temporary and fixed blood donation facilities, blood banks, and blood processing centers, was designed regarding the deteriorating nature of blood. The proposed model was applied in a real case in Urmia, Iran. The numerical results and sensitivity analysis of the key model parameters ensured the applicability of the proposed model.

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