Mathematical Programming for Modelling Green Supply Chains Under Randomness and Fuzziness

2017 ◽  
Vol 6 (1) ◽  
pp. 56-85
Author(s):  
Javad Nematian ◽  
Seyed Salar Ghotb
Keyword(s):  
Supply Chains ◽  
Deterministic Model ◽  
Negative Impact ◽  
Fuzzy Theory ◽  
Mixed Integer ◽  
Chance Constrained Programming ◽  
Proposed Model ◽  
Constrained Programming ◽  
Green Supply Chains ◽  
Fuzzy Random

Nowadays by growing concerns about environmental problems, businesses and industries are under pressure to decrease their negative impact on environment, consequently firms and industries have to reconsider about their activities and make their business compatible with environment. So industries should green their supply chains to optimize economic and environmental concerns, but because of uncertainty in the real world like inconsistency of world economy, the process of greening supply chains can be more complex. To optimize total costs and the unfavourable sides of supply chains simultaneously in an uncertain situation, this paper presents a multi-objective mixed integer programming with fuzzy random variables (FRVs) and by using fuzzy theory and fuzzy random chance-constrained programming (FRCCP), the proposed model is converted to deterministic model. This paper can be also suitable for decision making with optimistic, pessimistic and realistic notion. Finally, a numerical example is presented to illustrate the model.

scholarly journals The Identification of Sustainable Supply Chain Elements in The Enterprise X

2013 ◽  
Vol 5 (1) ◽  
pp. 23-27
Author(s):  
Paula Bajdor
Keyword(s):  
Economic Development ◽  
Supply Chain ◽  
Supply Chains ◽  
Social Environment ◽  
Natural Environment ◽  
Negative Impact ◽  
Research Purpose ◽  
Sustainable Supply Chain ◽  
Green Supply Chains ◽  
Further Development

Abstract Today, operating on the market, enterprises, to a lesser or greater extent, try to carry out their activities in such a way to minimize the possible negative impact on the environment. In most companies, the analysis of its supply chains can identify them as "green supply chains", which primarily involves not harming the natural environment. However, the further development of this concept is "sustainable supply chain", the chain that means not only protection of the environment but also means caring for the closest social environment together with economic development of the company. As opposed to green supply chains, it is still difficult to identify a sustainable supply chain in Polish enterprises. For the research purpose, the interview sheet has been created, based on the answers provided by the companies it is possible to further identify and determine the elements that make up a sustainable supply chain. This article presents an interview sheet with the answers given by one of the companies investigated

scholarly journals Fuzzy Random Chance-Constrained Programming Model for the Vehicle Routing Problem of Hazardous Materials Transportation

Symmetry ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 1208
Author(s):  
Liying Zhao ◽  
Ningbo Cao
Keyword(s):  
Risk Model ◽  
Programming Model ◽  
Hazardous Materials ◽  
Theory Model ◽  
Chance Constrained Programming ◽  
Daily Routine ◽  
Vehicle Speed ◽  
Vehicle Route ◽  
Constrained Programming ◽  
Fuzzy Random

As an indispensable necessity in daily routine of citizens, hazardous materials (Hazmat) not only plays an increasingly important role, but also brings a series of transportation uncertainty phenomena, the most prominent of which is a safety problem. When it attempts to find the best vehicle route scheme that can possess the lowest risk attribute in a fuzzy random environment for a single warehouse, the influence of cost should also be taken into account. In this study, a new mathematical theory was conducted in the modeling process. To take a full consideration of uncertainty, vehicle travel distance and population density along the road segment were assumed to be fuzzy variables. Meanwhile, accident probability and vehicle speed were set to be stochastic. Furthermore, based on the assumptions, authors established three chance constrained programming models according to the uncertain theory. Model I was used to seek the achievement of minimum risk of the vehicle route scheme, using traditional risk model; the goal of Model II was to obtain the lowest total cost, including the green cost, and the main purpose of Model III was to establish a balance between cost and risk. To settle the above models, a hybrid intelligent algorithm was designed, which was a combination of genetic algorithm and fuzzy random simulation algorithm, which simultaneously proved its convergence. At last, two experiments were designed to illustrate the feasibility of the proposed models and algorithms.

End-of-Life Decision Making With Uncertain Product Return Quantity

2012 ◽  
Vol 134 (10) ◽  
Author(s):  
Sara Behdad ◽  
Aida Sefic Williams ◽  
Deborah Thurston
Keyword(s):  
End Of Life ◽  
Programming Model ◽  
Electronic Waste ◽  
Mixed Integer ◽  
Chance Constrained Programming ◽  
Resource Requirements ◽  
Stochastic Programming Model ◽  
Constrained Programming ◽  
End Of Life Decision ◽  
High Degree

The management of end-of-life electronic waste (e-waste) attracts significant attention due to environmental concerns, legislative requirements, consumer interest in green products, and the market image of manufacturers. However, managing e-waste is complicated by several factors, including the high degree of uncertainty of quantity, timing of arrival, and quality of the returned products. This variability in the stream of returned end-of-life (EOL) products makes it difficult to plan for remanufacturing facility materials, equipment, and human resource requirements. The aim of this research is to tackle the uncertainty associated with the quantity of received used products. A stochastic programming model for waste stream acquisition systems (as opposed to market-driven systems) is introduced. The model considers the quantity of returned product as an uncertain parameter and determines to what extent the product should be disassembled and what is the best EOL option for each subassembly. The stochastic model is defined in a form of chance constrained programming and is then converted to a mixed integer linear programming. An example is provided to illustrate the application of the model for an uncertain stream of PCs (minus monitor and keyboard) received in a PC refurbishing company. The remanufacturer must then decide which proportion of disassembled modules should be processed given specific remanufacturing options.

scholarly journals Optimization of CCUS Supply Chains for Some European Countries under the Uncertainty

Processes ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 960
Author(s):  
Grazia Leonzio ◽  
Pier Ugo Foscolo ◽  
Edwin Zondervan
Keyword(s):  
Carbon Dioxide ◽  
Stochastic Model ◽  
Supply Chains ◽  
Carbon Dioxide Emissions ◽  
Deterministic Model ◽  
Numerical Models ◽  
Production Costs ◽  
Mixed Integer ◽  
The Uk ◽  
And Storage

This paper develops a two-stage stochastic mixed integer linear programming model to optimize Carbon Capture, Utilization and Storage (CCUS) supply chains in Italy, Germany and the UK. Few works are present in the literature about this topic, thus this paper overcomes this limitation considering carbon supply chains producing different products. The objective of the numerical models is to minimize expected total costs, under the uncertainties of the production costs of carbon-dioxide-based compounds. Once carbon dioxide emissions that should be avoided are fixed, according to environmental protection requirements for each country, the optimal design of these supply chains is obtained finding the distribution of carbon dioxide captured between utilization and storage sections, the amount of different carbon-based products and the best connection between each element inside the system. The expected total costs for the CCUS supply chain of Italy, Germany and the UK are, respectively, 77.3, 98.0 and 1.05 billion€/year (1004, 613 and 164 €/ton CO2 captured). A comparison with the respective deterministic model, analyzed elsewhere, is considered through the evaluation of the Expected Value of Perfect Information (EVPI) and the Value of Stochastic Solution (VSS). The former is 1.29 billion€/year, 0.18 million€/year and 8.31 billion€/year, respectively, for the CCUS of Italy, the UK and Germany. VSS on the other hand is equal to 1.56 billion€/year, 0 €/year and 0.1 billion€/year, respectively, for the frameworks of Italy, the UK and Germany. The results show that the uncertain production cost in the stochastic model does not have a significant effect on the results; thus, in this case, there are few advantages in solving a stochastic model instead of the deterministic one.

scholarly journals A Two-Stage Optimal Scheduling Model of Microgrid Based on Chance-Constrained Programming in Spot Markets

Processes ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. 107 ◽  
Author(s):  
Li ◽  
Tan ◽  
Ren ◽  
Yang ◽  
Yu ◽  
...  
Keyword(s):  
Pso Algorithm ◽  
Spot Market ◽  
Optimal Scheduling ◽  
Spot Markets ◽  
Chance Constrained Programming ◽  
Two Stage ◽  
Market Prices ◽  
Scheduling Model ◽  
Proposed Model ◽  
Constrained Programming

Aimed at the coordination control problem of each unit caused by microgrid participation in the spot market and considering the randomness of wind and solar output and the uncertainty of spot market prices, a day-ahead real-time two-stage optimal scheduling model for microgrid was established by using the chance-constrained programming theory. On this basis, an improved particle swarm optimization (PSO) algorithm based on stochastic simulation technology was used to solve the problem and the effect of demand side management and confidence level on scheduling results is discussed. The example results verified the correctness and effectiveness of the proposed model, which can provide a theoretical basis in terms of reasonably coordinating the output of each unit in the microgrid in the spot market.

scholarly journals A Multi-objective MILP Model Proposed to Optimize a Supply Chain Network for Microalgae-based Biofuels and Co-products: A Case Study in Iran

2021 ◽  
Author(s):  
Mohammad Ehsan Zerafati ◽  
Ali Bozorgi-Amiri ◽  
Amir-Mohammad Golmohammadi ◽  
Fariborz Jolai
Keyword(s):  
Supply Chain ◽  
Objective Function ◽  
Environmental Impacts ◽  
Deterministic Model ◽  
Mixed Integer ◽  
Supply Chain Network ◽  
Multi Objective ◽  
Proposed Model ◽  
Milp Model

Abstract Recently, due to the efficiency of cultivating microalgae, researchers and investors have paid considerable attention to the production of different biofuel products that are environmentally friendly. In this study, a two-stage deterministic model is proposed to design a microalgae-based biofuels and co-products supply chain network (MBCSCN). In the first stage, the appropriate locations for the cultivation of microalgae are identified through the analytical hierarchy process (AHP). In the second stage, a deterministic mathematical mixed integer linear programing (MILP) model is developed for a period of five years based on the criteria of economic and environmental impacts. The economic objective function maximizes the overall profit, while the environmental impacts objective function seeks to minimize the consumed fossil fuel throughout the supply chain. Then, a multi-objective MILP optimization problem is solved using the ε-constraint method. The proposed model is evaluated through a case study in Iran. It has helped to identify appropriate locations for the cultivation of microalgae and to specify the required quantity of feedstock, the species of microalgae, the required technology, and the transportation modes in each step of the supply chain.

scholarly journals Pricing and Warranty Decisions of Substitutable Products for a Fuzzy Two-Echelon Supply Chain

2017 ◽  
Vol 2017 ◽  
pp. 1-12
Author(s):  
Yongzhao Wang
Keyword(s):  
Supply Chain ◽  
Fuzzy Theory ◽  
Chance Constrained Programming ◽  
Fuzzy Variables ◽  
Closed Form Solutions ◽  
Substitutable Products ◽  
Game Theoretical Approach ◽  
Warranty Costs ◽  
Constrained Programming ◽  
Warranty Service

This paper considers the optimal decisions of pricing and warranty level for substitutable products in a fuzzy supply chain environment, where the consumer demands, manufacturing costs, and warranty costs are characterized as fuzzy variables. Expected value manufacturer-leader Stackelberg models and two chance-constrained programming models, that is, theλ-optimistic andλ-pessimistic manufacturer-leader Stackelberg models, are established. The corresponding closed-form solutions are obtained by using the game-theoretical approach and fuzzy theory. Finally, numerical examples are presented to illustrate the effectiveness of the models and to provide managerial insights for decision makers. The results show that it would be beneficial for the whole supply chain when the warranty services are introduced into the market, and the firm which provides the warranty service has the advantage in holding more dominant position.

Mixed Chance Constrained Unit Commitment Model for Power System Containing Wind Farm

2014 ◽  
Vol 644-650 ◽  
pp. 3850-3853
Author(s):  
Si Qing Sheng ◽  
Xiao Xia Sun
Keyword(s):  
Power System ◽  
Prediction Error ◽  
Wind Farm ◽  
Unit Commitment ◽  
Fuzzy Variable ◽  
Random Variable ◽  
Chance Constrained Programming ◽  
Load Prediction ◽  
Proposed Model ◽  
Constrained Programming

This paper presents a new unit commitment model to solve the uncertainty of wind and load. The chance constrained programming is introduced in this paper. The uncertainty of wind and load is expressed as their prediction error. Considering their different characteristic, wind prediction error is indicated as a fuzzy variable, while load prediction error is represented as random variable. Different confidences reflect the different satisfaction of the constraints. Finally, example analysis shows that the proposed model is feasible and effectiveness.

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