scholarly journals Optimal inventory policy in a closed loop supply chain system with multiple periods

2017 ◽  
Vol 10 (2) ◽  
pp. 237 ◽  
Author(s):  
SasiKumar A. ◽  
Natarajan K ◽  
Ramasubramaniam MuthuRathna Sapabathy ◽  
Deepaknallasamy K.K
Keyword(s):  
Supply Chain ◽  
Closed Loop ◽  
Mixed Integer ◽  
Order Quantity ◽  
Reverse Supply Chain ◽  
Supply Chain System ◽  
Inventory Policy ◽  
Closed Loop Supply Chain ◽  
Proposed Model ◽  
Fixed Order

Purpose: This paper aims to model and optimize the closed loop supply chain for maximizing the profit by considering the fixed order quantity inventory policy in various sites at multiple periods.Design/methodology/approach: In forward supply chain, a standard inventory policy can be followed when the product moves from manufacturer, distributer, retailer and customer but the inventory in the reverse supply chain of the product with the similar standard policy is very difficult to manage. This model investigates the standard policy of fixed order quantity by considering the three major types of return-recovery pair such as commercial returns, end- of- use returns, end –of- life returns and their inventory positioning at multiple periods.  The model is configured as mixed integer linear programming and solved by IBM ILOG CPLEX OPL studio.Findings: To find the performance of the model a numerical example is considered for a product with three Parts (A which of 2nos, B and C) for 12 multiple periods. The results of the analysis show that the manufacturer can know how much should to be manufacture in multiple periods based on Variations of the demand by adopting the FOQ inventory policy at different sites considering its capacity constraints. In addition, it is important how much of parts should be purchased from the supplier at the given 12 periods.Originality/value: A sensitivity analysis is performed to validate the proposed model two parts. First part of the analysis will focus on the inventory of product and parts and second part of analysis focus on profit of the company. The analysis which provides some insights in to the structure of the model.

A Mixed-Integer Linear Programming Model of Closed Loop Supply Chain Network for Manufacturing System

2018 ◽  
Vol 35 ◽  
pp. 198-207 ◽  
Author(s):  
S. Nallusamy ◽  
K. Balakannan ◽  
P.S. Chakraborty ◽  
Gautam Majumdar
Keyword(s):  
Linear Programming ◽  
Supply Chain ◽  
Mixed Integer Linear Programming ◽  
Closed Loop ◽  
Programming Model ◽  
Mixed Integer ◽  
Order Quantity ◽  
Integer Linear Programming Model ◽  
Proposed Model ◽  
Fixed Order

In the present scheme of things, in a manufacturing industry inventory is pitched as one of the significant resources that require to be handled effectively. The aim of this research article is to develop a mixed-integer linear programming model to configure the closed loop supply chain (CLSC) network and that could be optimized for maximizing the profit by determining the fixed order quantity inventory policy in various sites at multiple periods. The objective is to maximize the profit through CLSC by determining the optimal inventory of product and part mix during multiple periods. In onward supply chain, a standard inventory policy is followed when the product moves from manufacturer to end user, but it is very difficult to manage the inventory in the reverse supply chain of the product with the same standard policy. The proposed model examines the standard policy of fixed order quantity by considering three major types of return-recovery pair such as, commercial returns, end-of-use returns, end-of-life returns and their inventory positioning at multiple periods. Raw material supplier, manufacturer, distributer, retailer, customers and for major returns-collection sites like repair site, disassembly site, recycling site and disposal site were included in the network to develop this CLSC network model. The proposed model to configure the CLSC network has been solved by using IBM ILOG CPLEX OPL studio and the results of the model were analysed with numerical investigations followed by sensitivity analysis.

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 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 Closed-Loop Supply Chain Design with Sustainability Aspects and Network Resilience under Uncertainty: Modelling and Application

2021 ◽  
Vol 2021 ◽  
pp. 1-23
Author(s):  
Komeyl Baghizadeh ◽  
Julia Pahl ◽  
Guiping Hu
Keyword(s):  
Supply Chain ◽  
Closed Loop ◽  
Optimal Solution ◽  
Supply Chain Design ◽  
Mixed Integer ◽  
Distribution Centers ◽  
Closed Loop Supply Chain ◽  
Proposed Model ◽  
Network Flexibility ◽  
Uncertainty Parameters

In this study, we present a multiobjective mixed-integer nonlinear programming (MINLP) model to design a closed-loop supply chain (CLSC) from production stage to distribution as well as recycling for reproduction. The given network includes production centers, potential points for establishing of distribution centers, retrieval centers, collecting and recycling centers, and the demand points. The presented model seeks to find optimal locations for distribution centers, second-hand product collection centers, and recycling centers under the uncertainty situation alongside the factory’s fixed points. The purpose of the presented model is to minimize overall network costs including processing, establishing, and transportation of products and return flows as well as environmental impacts while maximizing social scales and network flexibility according to the presence of uncertainty parameters in the problem. To solve the proposed model with fuzzy uncertainty, first, the improved epsilon (ε)-constraints approach is used to transform a multiobjective to a single-objective problem. Afterward, the Lagrangian relaxation approach is applied to effectively solve the problem. A real-world case study is used to evaluate the performance of the proposed model. Finally, sensitivity analysis is performed to study the effects of important parameters on the optimal solution.

scholarly journals A multi-objective optimal decision model for a green closed-loop supply chain under uncertainty: A real industrial case study

2021 ◽  
Vol 16 (2) ◽  
pp. 161-172
Author(s):  
I.W. Fang ◽  
W.-T. Lin
Keyword(s):  
Supply Chain ◽  
Closed Loop ◽  
Resource Scarcity ◽  
Mixed Integer ◽  
Optimal Decision ◽  
Quality Level ◽  
Chain Model ◽  
Closed Loop Supply Chain ◽  
Multi Objective ◽  
Proposed Model

Green closed-loop supply chain management is an important topic for business operations today because of increasing resource scarcity and environmental issues. Companies not only have to meet environmental regulations, but also must ensure high quality supply chain operation as a means to secure competitive advantages and increase profits. This study proposes a multi-objective mixed integer programming model for an integrated green closed-loop supply chain network designed to maximize profit, amicable production level (environmentally friendly materials and clean technology usage), and quality level. A scenario-based robust optimization method is used to deal with uncertain parameters such as the demand of new products, the return rates of returned products and the sale prices of remanufactured products. The proposed model is applied to a real industry case example of a manufacturing company to illustrate the applicability of the proposed model. The result shows a robust optimal resource allocation solution that considers multiple scenarios. This study can be a reference for closed-loop supply chain related academic research and also can be used to guide the development of a green closed-loop supply chain model for better decision making.

scholarly journals A mathematical model for designing a reliable cellular hybrid manufacturing-remanufacturing system considering alternative and contingency process routings

2021 ◽  
Vol 3 (3) ◽  
Author(s):  
Amirreza Hooshyar Telegraphi ◽  
Akif Asil Bulgak
Keyword(s):  
Mathematical Model ◽  
Supply Chain ◽  
Manufacturing Systems ◽  
Closed Loop ◽  
Sustainable Manufacturing ◽  
Critical Issue ◽  
Economic Benefits ◽  
Mixed Integer ◽  
Hybrid Manufacturing ◽  
Closed Loop Supply Chain

AbstractDue to the stringent awareness toward the preservation and resuscitation of natural resources and the potential economic benefits, designing sustainable manufacturing enterprises has become a critical issue in recent years. This presents different challenges in coordinating the activities inside the manufacturing systems with the entire closed-loop supply chain. In this paper, a mixed-integer mathematical model for designing a hybrid-manufacturing-remanufacturing system in a closed-loop supply chain is presented. Noteworthy, the operational planning of a cellular hybrid manufacturing-remanufacturing system is coordinated with the tactical planning of a closed-loop supply chain. To improve the flexibility and reliability in the cellular hybrid manufacturing-remanufacturing system, alternative process routings and contingency process routings are considered. The mathematical model in this paper, to the best of our knowledge, is the first integrated model in the design of hybrid cellular manufacturing systems which considers main and contingency process routings as well as reliability of the manufacturing system.

scholarly journals A fuzzy approach to multi-objective mixed integer linear programming model for multi-echelon closed-loop supply chain with multi-product multi-time-period

2020 ◽  
Vol 30 (1) ◽  
Author(s):  
Sema Akin Bas ◽  
Beyza Ahlatcioglu Ozkok
Keyword(s):  
Linear Programming ◽  
Supply Chain ◽  
Integer Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Closed Loop ◽  
Mixed Integer ◽  
Fuzzy Approach ◽  
Closed Loop Supply Chain ◽  
Multi Objective ◽  
Time Period

By the green point of view, supply chain management (SCM), which contains supplier and location selection, production, distribution, and inventory decisions, is an important subject being examined in recent years by both practitioners and academicians. In this paper, the closed-loop supply chain (CLSC) network that can be mutually agreed by meeting at the level of common satisfaction of conflicting objectives is designed. We construct a multi-objective mixed-integer linear programming (MOMILP) model that allows decision-makers to more effectively manage firms’ closed-loop green supply chain (SC). An ecological perspective is brought by carrying out the recycling, remanufacturing and destruction to SCM in our proposed model. Maximize the rating of the regions in which they are located, minimize total cost and carbon footprint are considered as the objectives of the model. By constructing our model, the focus of customer satisfaction is met, as well as the production, location of facilities and order allocation are decided, and we also carry out the inventory control of warehouses. In our multi-product multi-component multi-time-period model, the solution is obtained with a fuzzy approach by using the min operator of Zimmermann. To illustrate the model, we provide a practical case study, and an optimal result containing a preferable level of satisfaction to the decision-maker is obtained.

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.

scholarly journals Warranty Period Decision and Coordination in Closed-Loop Supply Chains Considering Remanufacturing and Consumer Behavior

2019 ◽  
Vol 11 (15) ◽  
pp. 4237 ◽  
Author(s):  
Xiaodong Zhu ◽  
Lingfei Yu ◽  
Wei Li
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Supply Chains ◽  
Closed Loop ◽  
Supply Chain System ◽  
Closed Loop Supply Chain ◽  
Chain System ◽  
Warranty Period ◽  
Closed Loop Supply Chains ◽  
Decision Making Model

The closed-loop supply chain management model is an effective way to promote sustainable economic development and environmental protection. Increasing the sales volume of remanufactured products to stimulate green growth is a key issue in the development of closed-loop supply chains. By designing an effective warranty strategy, customer’s perceived value can be enhanced and market demand can be stimulated. This study cuts through the warranty period of closed-loop supply chain products. Based on the perspective of consumer behavior, game theory is used to construct the optimal decision-making model for closed-loop supply chains. The optimal warranty decision making for new products and remanufactured products under centralized and decentralized decision-making models is discussed. Further, the impact of the closed-loop supply chain system with warranty services and the design of contract coordination is also shown. We show that consumer preference has a positive impact on the sales of remanufactured products and the profits of enterprises; with the extension of the new product and remanufacturing warranty period, the profit of the supply chain system first increases and then decreases, and the value is maximized at the extreme point in the manufacturer-led decision-making model. Furthermore, the leader gains higher profits with bargaining power, but the profit of the supply chain system under decentralized decision model is less than that of the centralized decision model, reflecting the double marginalization effect. The revenue sharing contract and the two-charge contract designed in this study coordinate the closed-loop supply chain system with warranty services, so that the member companies in the supply chain can achieve Pareto improvement.

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