Robust optimization model for sustainable supply chain for production and distribution of polyethylene pipe

2020 ◽  
Vol 15 (4) ◽  
pp. 1613-1653
Author(s):  
Jaber Valizadeh ◽  
Ehsan Sadeh ◽  
Zainolabedin Amini Sabegh ◽  
Ashkan Hafezalkotob
Keyword(s):  
Genetic Algorithm ◽  
Supply Chain ◽  
Environmental Impacts ◽  
Closed Loop ◽  
Optimal Location ◽  
Computational Time ◽  
Closed Loop Supply Chain ◽  
Content Type ◽  
Proposed Model ◽  
Production And Distribution

Purpose In this study, the authors consider the key decisions in the design of the green closed-loop supply chain (CSLC) network. These decisions include considering the optimal location of suppliers, production facilities, distribution, customers, recycling centers and disposal of non-recyclable goods. In the proposed model, the level of technology used in recycling and production centers is taken into account. Moreover, in this paper is the environmental impacts of production and distribution of products based on the eco-indicator 99 are considered. Design/methodology/approach In this study, the author consider the key decisions in the design of the green CLSC network. These decisions include considering the optimal location of suppliers, production facilities, distribution, customers, recycling centers and disposal of non-recyclable goods. In the proposed model, the level of technology used in recycling and production centers is taken into account. Moreover, the environmental impacts of production and distribution of products based on the eco-indicator 99 are considered. Findings The results indicate that the results obtained from the colonial competition algorithm have higher quality than the genetic algorithm. This quality of results includes relative percentage deviation and computational time of the algorithm and it is shown that the computational time of the colonial competition algorithm is significantly lower than the computational time of the genetic algorithm. Furthermore, the limit test and sensitivity analysis results show that the proposed model has sufficient accuracy. Originality/value Solid modeling of the green supply chain of the closed loop using the solid optimized method by Bertsimas and Sim. Development of models that considered environmental impacts to the closed loop supply chain. Considering the impact of the technology type in the manufacture of products and the recycling of waste that will reduce emissions of environmental pollutants. Another innovation of the model is the multi-cycle modeling of the closed loop of supply chain by considering the uncertainty and the fixed and variable cost of transport.

Multi-objective robust optimization for multi-stage-multi-product agile closed-loop supply chain under uncertainty in the context of circular economy

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Saeid Jafarzadeh Ghoushchi ◽  
Iman Hushyar ◽  
Kamyar Sabri-Laghaie
Keyword(s):  
Supply Chain ◽  
Robust Optimization ◽  
Circular Economy ◽  
Closed Loop ◽  
Mixed Integer ◽  
Closed Loop Supply Chain ◽  
Content Type ◽  
Multi Objective ◽  
Multi Stage ◽  
Proposed Model

PurposeA circular economy (CE) is an economic system that tries to eliminate waste and continually use resources. Due to growing environmental concerns, supply chain (SC) design should be based on the CE considerations. In addition, responding and satisfying customers are the challenges managers constantly encounter. This study aims to improve the design of an agile closed-loop supply chain (CLSC) from the CE point of view.Design/methodology/approachIn this research, a new multi-stage, multi-product and multi-period design of a CLSC network under uncertainty is proposed that aligns with the goals of CE and SC participants. Recycling of goods is an important part of the CLSC. Therefore, a multi-objective mixed-integer linear programming model (MILP) is proposed to formulate the problem. Besides, a robust counterpart of multi-objective MILP is offered based on robust optimization to cope with the uncertainty of parameters. Finally, the proposed model is solved using the e-constraint method.FindingsThe proposed model aims to provide the strategic choice of economic order to the suppliers and third-party logistic companies. The present study, which is carried out using a numerical example and sensitivity analysis, provides a robust model and solution methodology that are effective and applicable in CE-related problems.Practical implicationsThis study shows how all upstream and downstream units of the SC network must work integrated to meet customer needs considering the CE context.Originality/valueThe main goal of the CE is to optimize resources, reduce the use of raw materials, and revitalize waste by recycling. In this study, a comprehensive model that can consider both SC design and CE necessities is developed that considers all SC participants.

scholarly journals Designing a New Multi-Echelon Multi-Period Closed-Loop Supply Chain Network by Forecasting Demand Using Time Series Model: A Genetic Algorithm

2022 ◽  
Author(s):  
Shahab Safaei ◽  
Peiman Ghasemi ◽  
Fariba Goodarzian ◽  
Mohsen Momenitabar
Keyword(s):  
Genetic Algorithm ◽  
Time Series ◽  
Supply Chain ◽  
Closed Loop ◽  
Critical Role ◽  
Time Series Model ◽  
Supply Chain Network ◽  
Distribution Centers ◽  
Closed Loop Supply Chain ◽  
Proposed Model

Abstract In the closed-loop supply chain, demand plays a critical role. The flow of materials and commodities in the opposite direction of the normal chain is inevitable too. So, in this paper, a new multi-echelon multi-period closed-loop supply chain network is addressed to minimize the total costs of the network. The considered echelons include suppliers, manufacturers, distribution centers, customers, and recycling and recovery units of components in the proposed network. Also, a linear programming model considering factories' vehicles and rental cars of transportation companies is formulated for the proposed problem. Moreover, the products demand is predicted by Auto-Regressive Integrated Moving Average (ARIMA) time series model to decrease the amount of shortage may happens in the network. To solve the proposed model, GAMS software is used in small-sized problems and a genetic algorithm in large-sized problems is employed. Numerical results show that the proposed model is closer to the real situation and the proposed solution method is efficient. Accordingly, sensitivity analysis is performed on important parameters to show the performance of the proposed model.

A multi-objective mixed-integer linear model for sustainable fruit closed-loop supply chain network

2020 ◽  
Vol 31 (5) ◽  
pp. 1351-1373
Author(s):  
Younis Jabarzadeh ◽  
Hossein Reyhani Yamchi ◽  
Vikas Kumar ◽  
Nader Ghaffarinasab
Keyword(s):  
Supply Chain ◽  
Closed Loop ◽  
Environmental Indicators ◽  
Mixed Integer ◽  
Computational Time ◽  
Distribution Centers ◽  
Closed Loop Supply Chain ◽  
Content Type ◽  
Multi Objective ◽  
Lp Metric

PurposeThis paper aims to present a closed-loop supply chain (CLSC) optimization problem for a perishable agricultural product to achieve three pillars of sustainability, including minimizing total network costs and carbon dioxide emissions from different network activities and maximizing responsiveness to demands simultaneously.Design/methodology/approachThe research problem is formulated as a multi-objective mixed-integer linear programming model, and classical approaches, including the LP-Metric and weighted Tchebycheff method, have been applied to solve the optimization model. A set of test problems has been proposed to validate the model, and the results are presented.FindingsComputational time to find Pareto optimal solutions by using the weighted Tchebycheff method was twice as much as that of the LP-Metric method. Also, the result of the study is a mathematical model that can be applied to other products that are close to the fruit, such as vegetables.Research limitations/implicationsThe present study is limited to fruits supply chains and the inventory is considered at the distribution centers only. The study also considers only one type of transport.Practical implicationsThe paper can assist supply chain managers to define strategies to achieve a sustainable CLSC network configuration for the fruits.Originality/valueThis study is one of the early studies to consider environmental indicators in fruits supply chain design along with two other indicators of sustainability, namely, economic and social indicators. Therefore, this can help supply chain managers to achieve sustainability by optimizing location decisions, inventory quantities and flow between facilities.

An eco-friendly closed loop supply chain network with multi-facility allocated centralized depots for bidirectional flow in a battery manufacturing industry

2019 ◽  
Vol 17 (1) ◽  
pp. 131-159
Author(s):  
S. Umar Sherif ◽  
P. Sasikumar ◽  
P. Asokan ◽  
J. Jerald
Keyword(s):  
Supply Chain ◽  
Manufacturing Industry ◽  
Closed Loop ◽  
Research Work ◽  
Supply Chain Network ◽  
Closed Loop Supply Chain ◽  
Content Type ◽  
Proposed Model ◽  
Bidirectional Flow ◽  
Single Objective

Purpose Due to the economic benefits and environmental awareness, most of the battery manufacturing industries in India are interested to redesign their existing supply chain network or to incorporate the effective closed loop supply chain network (CLSCN). The purpose of this paper is to develop CLSCN model with eco-friendly distribution network and also enhance recycling to utilize recycled lead for new battery production. The existing CLSCN model of a battery manufacturing industry considered for case study is customized for attaining economic benefit and environmental safety. Hence, single objective, multi-echelon, multi-period and multi-product CLSCN model with centralized depots (CD) is developed in this work to maximize the profit and reduce the emission of CO2 in transportation. Design/methodology/approach The proposed CD has the facility to store new batteries (NB), scrap batteries (SB) and lead ingot. The objective of the proposed research work is to identify potential location of CD using K-means clustering algorithm, to allocate facilities with CD using multi-facility allocation (MFA) algorithm and to minimize overall travel distance by allowing bidirectional flow of materials and products between facilities. The proposed eco-friendly CLSCN-CD model is solved using GAMS 23.5 for optimal solutions. Findings The performance of the proposed model is validated by comparing with existing model. The evaluation reveals that the proposed model is better than the existing model. The sensitivity analysis is demonstrated with different rate of return of SB, different proportion of recycled lead and different type of vehicles, which will help the management to take appropriate decision in the context of cost savings. Originality/value This research work has proposed single objective, multi echelon, multi period and multi product CLSCN-CD model in the battery manufacturing industry to maximize the profit and reduce the CO2 emission in transportation, by enhancing the bidirectional flow of materials/products between facilities of entire model.

Optimization of virtual closed-loop supply chain under uncertainty: application of IoT

Kybernetes ◽  
2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hanieh Shambayati ◽  
Mohsen Shafiei Nikabadi ◽  
Seyed Mohammad Ali Khatami Firouzabadi ◽  
Mohammad Rahmanimanesh ◽  
Sara Saberi
Keyword(s):  
Supply Chain ◽  
Energy Consumption ◽  
Firefly Algorithm ◽  
Closed Loop ◽  
Mathematical Optimization ◽  
Grey Wolf ◽  
Closed Loop Supply Chain ◽  
Content Type ◽  
Proposed Model ◽  
Grey Wolf Algorithm

PurposeSupply chains (SCs) have been growingly virtualized in response to the market challenges and opportunities that are presented by new and cost-effective internet-based technologies today. This paper designed a virtual closed-loop supply chain (VCLSC) network based on multiperiod, multiproduct and by using the Internet of Things (IoT). The purpose of the paper is the optimization of the VCLSC network.Design/methodology/approachThe proposed model considers the maximization of profit. For this purpose, costs related to virtualization such as security, energy consumption, recall and IoT facilities along with the usual costs of the SC are considered in the model. Due to real-world demand fluctuations, in this model, demand is considered fuzzy. Finally, the problem is solved using the Grey Wolf algorithm and Firefly algorithm. A numerical example and sensitivity analysis on the main parameters of the model are used to describe the importance and applicability of the developed model.FindingsThe findings showed that the Firefly algorithm performed better and identified more profit for the SC in each period. Also, the results of the sensitivity analysis using the IoT in a VCLSC showed that the profit of the virtual supply chain (VSC) is higher compared to not using IoT due to tracking defective parts and identifying reversible products. In proposed model, chain members can help improve chain operations by tracking raw materials and products, delivering products faster and with higher quality to customers, bringing a new level of SC efficiency to industries. As a result, VSCs can be controlled, programmed and optimized remotely over the Internet based on virtual objects rather than direct observation.Originality/valueThere are limited researches on designing and optimizing the VCLSC network. This study is one of the first studies that optimize the VSC networks considering minimization of virtual costs and maximization of profits. In most researches, the theory of VSC and its advantages have been described, while in this research, mathematical optimization and modeling of the VSC have been done, and it has been tried to apply SC virtualization using the IoT. Considering virtual costs in VSC optimization is another originality of this research. Also, considering the uncertainty in the SC brings the issue closer to the real world. In this study, virtualization costs including security, recall and energy consumption in SC optimization are considered.HighlightsInvestigates the role of IoT for virtual supply chain profit optimization and mathematical optimization of virtual closed-loop supply chain (VCLSC) based on multiperiod, multiproduct with emphasis on using the IoT under uncertainty.Considering the most important costs of virtualization of supply chain include: cost of IoT information security, cost of IoT energy consumption, cost of recall the production department, cost of IoT facilities.Selection of the optimal suppliers in each period and determination of the price of each returned product in virtual supply chain.Solving and validating the proposed model with two meta-heuristic algorithms (the Grey Wolf algorithm and Firefly algorithm).

Multi-objective multi-facility green manufacturing closed-loop supply chain under uncertain environment

2019 ◽  
Vol 39 (1) ◽  
pp. 58-76 ◽  
Author(s):  
Behzad Karimi ◽  
Amir Hossein Niknamfar ◽  
Babak Hassan Gavyar ◽  
Majid Barzegar ◽  
Ali Mohtashami
Keyword(s):  
Genetic Algorithm ◽  
Supply Chain ◽  
Closed Loop ◽  
Distribution Centers ◽  
Nsga Ii ◽  
Closed Loop Supply Chain ◽  
Content Type ◽  
Uncertain Environment ◽  
Multi Objective ◽  
Hierarchy Process

Purpose Today’s, supply chain production and distribution of products to improve the customer satisfaction in the shortest possible time by paying the minimum cost, has become the most important challenge in global market. On the other hand, minimizing the total cost of the transportation and distribution is one of the critical items for companies. To handle this challenge, this paper aims to present a multi-objective multi-facility model of green closed-loop supply chain (GCLSC) under uncertain environment. In this model, the proposed GCLSC considers three classes in case of the leading chain and three classes in terms of the recursive chain. The objectives are to maximize the total profit of the GCLSC, satisfaction of demand, the satisfactions of the customers and getting to the proper cost of the consumers, distribution centers and recursive centers. Design/methodology/approach Then, this model is designed by considering several products under several periods regarding the recovery possibility of products. Finally, to evaluate the proposed model, several numerical examples are randomly designed and then solved using non-dominated sorting genetic algorithm and non-dominated ranking genetic algorithm. Then, they are ranked by TOPSIS along with analytical hierarchy process so-called analytic hierarchy process-technique for order of preference by similarity to ideal solution (AHP-TOPSIS). Findings The results indicated that non-dominated ranked genetic algorithm (NRGA) algorithm outperforms non-dominated sorting genetic algorithm (NSGA-II) algorithm in terms of computation times. However, in other metrics, any significant difference was not seen. At the end, to rank the algorithms, a multi-criterion decision technique was used. The obtained results of this method indicated that NSGA-II had better performance than ones obtained by NRGA. Originality/value This study is motivated by the need of integrating the leading supply chain and retrogressive supply chain. In short, the highlights of the differences of this research with the mentioned studies are as follows: developing multi-objective multi-facility model of fuzzy GCLSC under uncertain environment and integrating the leading supply chain and retrogressive supply chain.

scholarly journals An Investigation on a Closed-Loop Supply Chain of Product Recycling Using a Multi-Agent and Priority Based Genetic Algorithm Approach

Mathematics ◽  
2020 ◽  
Vol 8 (6) ◽  
pp. 888
Author(s):  
Yong-Tong Chen ◽  
Zhong-Chen Cao
Keyword(s):  
Genetic Algorithm ◽  
Supply Chain ◽  
Closed Loop ◽  
Reverse Flow ◽  
Computational Time ◽  
Solution Quality ◽  
Closed Loop Supply Chain ◽  
Product Flow ◽  
Multi Agent ◽  
Product Recycling

Product recycling issues have gained increasing attention in many industries in the last decade due to a variety of reasons driven by environmental, governmental and economic factors. Closed-loop supply chain (CLSC) models integrate the forward and reverse flow of products. Since the optimization of these CLSC models is known to be NP-Hard, competition on optimization quality in terms of solution quality and computational time becomes one of the main focuses in the literature in this area. A typical six-level closed-loop supply chain network is examined in this paper, which has great complexity due to the high level of echelons. The proposed solution uses a multi-agent and priority based approach which is embedded within a two-stage Genetic Algorithm (GA), decomposing the problem into (i) product flow, (ii) demand allocation and (iii) pricing bidding process. To test and demonstrate the optimization quality of the proposed algorithm, numerical experiments have been carried out based on the well-known benchmarking network. The results prove the reliability and efficiency of the proposed approach compared to LINGO and the benchmarking algorithm discussed in the literature.

A multi-objective model for sustainable closed-loop supply chain of perishable products under two carbon emission regulations

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Saman Esmaeilian ◽  
Dariush Mohamadi ◽  
Majid Esmaelian ◽  
Mostafa Ebrahimpour
Keyword(s):  
Mathematical Model ◽  
Supply Chain ◽  
Life Cycle ◽  
Carbon Emission ◽  
Closed Loop ◽  
Perishable Products ◽  
Supply Chain Network ◽  
Closed Loop Supply Chain ◽  
Content Type ◽  
Trade Model

Purpose This paper aims to minimize the total carbon emissions and costs and also maximize the total social benefits. Design/methodology/approach The present study develops a mathematical model for a closed-loop supply chain network of perishable products so that considers the vital aspects of sustainability across the life cycle of the supply chain network. To evaluate carbon emissions, two different regulating policies are studied. Findings According to the obtained results, increasing the lifetime of the perishable products improves the incorporated objective function (IOF) in both the carbon cap-and-trade model and the model with a strict cap on carbon emission while the solving time increases in both models. Moreover, the computational efficiency of the carbon cap-and-trade model is higher than that of the model with a strict cap, but its value of the IOF is worse. Results indicate that efficient policies for carbon management will support planners to achieve sustainability in a cost-effectively manner. Originality/value This research proposes a mathematical model for the sustainable closed-loop supply chain of perishable products that applies the significant aspects of sustainability across the life cycle of the supply chain network. Regional economic value, regional development, unemployment rate and the number of job opportunities created in the regions are considered as the social dimension.

The Uncertain Programming of the Closed-Loop Supply Chain with Remanufacturing System

2012 ◽  
Vol 190-191 ◽  
pp. 218-221 ◽  
Author(s):  
Yu Juan Chen ◽  
Dong Bo Liu ◽  
Hong Wei Mao ◽  
Zi Qiang Zhang
Keyword(s):  
Supply Chain ◽  
Hybrid System ◽  
Closed Loop ◽  
Programming Model ◽  
Uncertain Programming ◽  
Fuzzy Simulation ◽  
Closed Loop Supply Chain ◽  
Proposed Model ◽  
Uncertain Model ◽  
Intelligent Optimization Algorithm

This paper addresses an integrated uncertain programming model for a closed-loop supply chain with manufacturing/remanufacturing hybrid system. The hybrid system is studied under the grey fuzzy uncertainty and grey uncertainty. The hybrid intelligent optimization algorithm integrating the grey fuzzy simulation, neural network and genetic algorithm can optimize the uncertain model. One numerical example is given to illustrate the effectiveness of the proposed model and algorithm.

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