scholarly journals Supply Interruption Supply Chain Network Model with Uncertain Demand: An Application of Chance-Constrained Programming with Fuzzy Parameters

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Haidong Guo ◽  
Shengyu Wang ◽  
Yu Zhang
Keyword(s):  
Supply Chain ◽  
Fuzzy Programming ◽  
Cost Effective ◽  
Chance Constrained Programming ◽  
Supply Chain Network ◽  
Fuzzy Constraints ◽  
Operation Rules ◽  
Supply Interruption ◽  
Constrained Programming ◽  
Fuzzy Parameters

The downstream supply interruption of manufacturers is a disaster for the company when the demand is uncertain in the market; a fuzzy programming with fuzzy parameters model of supply interruption supply chain network is established by simulating market operation rules. The aim of the current study is to build a fuzzy chance-constrained programming method which is developed for supporting the uncertainty of demand. This method ensured that the fuzzy constraints can be satisfied at specified confidence levels, leading to cost-effective solutions under acceptable risk magnitudes. Finally, through the case of the electronic product manufacturing enterprise, the feasibility and effectiveness of the proposed model are verified by adopting a sensitivity analysis of capacity loss level and minimizing objective function. Numerical simulation shows that selecting two manufacturing centers can effectively reduce the supply chain cost and maintain business continuity.

Designing a sustainable supply chain network for producing high-value products from waste glass

2021 ◽  
pp. 0734242X2199466
Author(s):  
Naeme Zarrinpoor
Keyword(s):  
Supply Chain ◽  
Greenhouse Gas Emission ◽  
Fuzzy Programming ◽  
Solution Procedure ◽  
Waste Glass ◽  
Worker Safety ◽  
Programming Approach ◽  
Supply Chain Network ◽  
Sustainable Supply Chain ◽  
Proposed Model

This paper aims to design a supply chain network for producing double glazed glass from the recycling of waste glass. All three pillars of sustainability are taken into consideration. The economic objective tries to maximize total profits. The environmental objective considers the energy consumption, the generated waste, the greenhouse gas emission, the water consumption, and the fuel consumption of vehicles. The social objective addresses created job opportunities, the worker safety, the regional development, the worker benefit, and training hours. To solve the model, a two-stage framework based on the group best-worst method and an interactive fuzzy programming approach is developed. The proposed model is validated through a real case study based on waste glass management in the city of Shiraz. It is revealed that when sustainable development goals are approached, a great degree of improvement will be attained in environmental and social aspects without a significant decrease in the economic sustainability. The results also demonstrate that the locations of glass recycling centres are different under economic, environmental, and social pillars, and the proposed model yields an optimal system configuration with a proper satisfaction degree of all objectives. Moreover, applying the proposed solution procedure enables system designers to obtain the most desirable trade-off between different aspects of sustainability.

A Fuzzy Programming Model of Supplier Selection

2012 ◽  
Vol 468-471 ◽  
pp. 668-673 ◽  
Author(s):  
Hua Jiang ◽  
Zhi Gang Lu
Keyword(s):  
Supplier Selection ◽  
Programming Model ◽  
Fuzzy Programming ◽  
Chance Constrained Programming ◽  
Hybrid Intelligent Algorithm ◽  
Fuzzy Variables ◽  
Fuzzy Expected Value ◽  
Order Quantities ◽  
Constrained Programming ◽  
Fuzzy Programming Model

An integrated supplier selection problem under fuzzy environment is studied in this paper. Firstly, the linear weight method is used to calculate the scores of suppliers according to their different attributes, such as: quality, service, warranty, delivery, reputation and position, which are assumed as fuzzy variables. Secondly, a fuzzy expected value programming model and a fuzzy chance-constrained programming model are proposed to select the best combination of the suppliers and determine the order quantities. A hybrid intelligent algorithm, based on fuzzy simulation, genetic algorithm and neural network, is used to solve the two models. Finally, a numerical example is given to illustrate the effectiveness of the proposed models.

Midterm Supply Chain Planning under Uncertainty: A Multiobjective Chance Constrained Programming Framework†

2008 ◽  
Vol 47 (15) ◽  
pp. 5501-5511 ◽  
Author(s):  
Kishalay Mitra ◽  
Ravindra D. Gudi ◽  
Sachin C. Patwardhan ◽  
Gautam Sardar
Keyword(s):  
Supply Chain ◽  
Chance Constrained Programming ◽  
Planning Under Uncertainty ◽  
Supply Chain Planning ◽  
Programming Framework ◽  
Constrained Programming

scholarly journals Green closed-loop supply chain network design: a novel bi-objective chance-constraint approach

2021 ◽  
Vol 55 (2) ◽  
pp. 811-840
Author(s):  
Amin Reza Kalantari Khalil Abad ◽  
Seyed Hamid Reza Pasandideh
Keyword(s):  
Supply Chain ◽  
Network Design ◽  
Closed Loop ◽  
Programming Model ◽  
Expected Value ◽  
Chance Constraint ◽  
Chance Constrained Programming ◽  
Supply Chain Network Design ◽  
Supply Chain Network ◽  
Closed Loop Supply Chain

In this paper, a novel chance-constrained programming model has been proposed for handling uncertainties in green closed loop supply chain network design. In addition to locating the facilities and establishing a flow between them, the model also determines the transportation mode between facilities. The objective functions are applied to minimize the expected value and variance of the total cost CO2 released is also controlled by providing a novel chance-constraint including a stochastic upper bound of emission capacity. To solve the mathematical model using the General Algebraic Modeling System (GAMS) software, four multi-objective decision-making (MODM) methods were applied. The proposed methodology was subjected to various numerical experiments. The solutions provided by different methods were compared in terms of the expected value of cost, variance of cost, and CPU time using Pareto-based analysis and optimality-based analysis. In Pareto-based analysis, a set of preferable solutions were presented using the Pareto front; then optimality-based optimization was chosen as the best method by using a Simple Additive Weighting (SAW) method. Experimental experiments and sensitivity analysis demonstrated that the performance of the goal attainment method was 13% and 24% better that of global criteria and goal programming methods, respectively.

A FUZZY PROGRAMMING APPROACH FOR SUPPLY CHAIN NETWORK DESIGN

2007 ◽  
Vol 15 (supp02) ◽  
pp. 75-87 ◽  
Author(s):  
XIAOYU JI ◽  
XIANDE ZHAO ◽  
DEMING ZHOU
Keyword(s):  
Supply Chain ◽  
Network Design ◽  
Cost Optimization ◽  
Fuzzy Programming ◽  
Network Design Problem ◽  
Programming Approach ◽  
Supply Chain Network Design ◽  
Supply Chain Network ◽  
Fuzzy Environment ◽  
Stochastic Parameters

This paper presents a fuzzy programming method to design supply chain network, in which the customer demands and transportation costs are assumed to be fuzzy parameters. Existing researches on supply chain network design problem are either restricted on deterministic environment or only address stochastic parameters. In this paper, we consider this problem in fuzzy environment. Under different criteria, we format three types of models for the decision makers: expected cost optimization model, chance-constrained model and chance maximization model. A genetic algorithm based on fuzzy simulation is developed to solve the proposed fuzzy models. Moreover, some numerical examples are presented to illustrate the effectiveness of models and solution algorithm.

Optimal Study of the Reverse Logistics Network for Municipal Solid Wastes

2014 ◽  
Vol 519-520 ◽  
pp. 1405-1411
Author(s):  
Zheng Zhang ◽  
Hui Min Ma
Keyword(s):  
Reverse Logistics ◽  
Programming Model ◽  
Solid Wastes ◽  
Chance Constrained Programming ◽  
Municipal Solid Wastes ◽  
Fuzzy Constraints ◽  
Logistics Network ◽  
Reverse Logistics Network ◽  
Constrained Programming ◽  
Fuzzy Parameter

A reverse logistics network for municipal solid wastes is designed. A fuzzy chance constrained programming model that the uncertain recovery quantity described by fuzzy parameter is put forward. The model is solved by transforming it to a deterministic mix integer linear programming model after making the fuzzy constraints clear. A numerical example is provided to demonstrate the feasibility of the model. And this paper analyzes the influence of different confidence level to the model.

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