Research on Optimization Method for Supply Chain Network Design under Uncertainty

Nowadays, the design of supply chain networks should be based on environmental issues as well as the needs of customers since the main driver of a supply chain network is customers. Continuous innovation of products requires understanding the features that are most important to customers, and product pricing should be carried out in a way that includes the satisfaction of both customers and manufacturers. This study uses the Kano model to classify product features into different categories. The design of the green supply chain network based on the Kano model has not been investigated in the literature so far. This study examines a green supply chain network including multiple manufacturers, product types, distributors, and carriers that is designed based on Kano’s conceptual model of multiple needs. In the proposed mathematical model of this paper, customer demand is a function of the selling price of the product, transportation pollution is minimized, and a solution based on the Cooperative Game Theory approach is used to solve the mathematical model using the GAMS software. One of the advantages of the proposed mathematical model in this research compared to other supply chain models is that the design needs of the supply chain network based on the Kano model (“must-be”, “one-dimensional”, “attractive” and “indifferent”) can be determined based on customer satisfaction. In addition, the price of the product can be determined according to the satisfaction of both customers and the manufacturers.

Designing a closed-loop supply chain network for citrus fruits crates considering environmental and economic issues

The design of robust value-creating supply chain networks: A critical review

Purpose The purpose of this paper is to design a sustainable supply chain network (SCN) for omnichannel environment in order to provide better service to customers through flexible distribution. Thus, there is a need to incorporate multiple-channel distribution in the network design of supply chains (SCs). Design/methodology/approach A multiple-channel distribution supply chain network (MCDSCN) has been proposed under omnichannel environment. This proposed model integrates online giants with local retailer’s distribution network in an uncertain environment with sustainability. To incorporate sustainability, an objective function is added to reduce carbon content along with other objectives of minimization of SC cost. The model turns out to be mixed-integer linear programming model which is coded in GAMS and solved using CPLEX solver. Findings The proposed MCDSCN model is compared with conventional SCN. Furthermore, it was found that the proposed MCDSCN model has achieved significant saving in SC cost and is also more sustainable than conventional SCN. The proposed model also enables online giants to integrate their distribution network with local retailer’s distribution network. Practical implications Through proposed model, customers are free to access product and services as per their choice of channels which increases their convenience, reach and satisfaction. Originality/value The proposed MCDSCN model is a novel approach to design flexible distribution systems. This would significantly help organizations to design their distribution network more effectively to meet global competition.

The ever-increasing concerns of the growth in the volume of waste tires, reduction in natural resources and new strict government legislations to reduce the environmental impact of the end-of-life (EOL) tires have increased interest among companies to design a sustainable and efficient closed-loop supply-chain (CLSC) network. A CLSC is a network with a holistic view of the entire forward and reverse logistic system with the aim of transferring the EOL products up the stream from the end users for value recovery such as reuse, repair, remanufacturing, or recycling.There are many factors that are considered when designing a closed-loop supply-chain network, such as uncertainty in the parameters, costs, environmental impacts, social dimensions, governmental regulations, domestic and international competition, disruption and operational risks, reliability of the network, technological advancements, etc. In the real world, the CLSC network design is subject to a variety of uncertainties which can be random and fuzzy. Designing a reliable and environmentally conscious CLSC which considers the risks and uncertainties of the parameters in the network is necessary for a successful supply-chain network. The government regulations could have a significant impact on the supply chain network design, its management and the long/short-term investment decisions. Ever-changing restrictions, mandates and tax policies can affect corporation's competitive advantage, market share, and operational costs. Tariffs and caps imposed on imported goods, intended to limit the volume of imports, protect domestic employment and reduce competition among domestic industries. One of the challenges facing the recovery of EOL products is the uncertainty associated with the conditions of the EOL products after being returned. Designing intelligent products that can collect valuable information during their life cycles is something that has been studied in the past decade. This information can be used to extend the life span of the products and improve the value recovery of EOL products. In this dissertation, we take a closer look at the challenges facing the tire industry and obtain a solution that creates a win-win situation for companies in the tire network as well as the environment. We evaluate the available recovery options for EOL tires, identify the uncertain parameters in the logistics network and find the solution for dealing with these uncertainties using robust modeling for the logistics network. In the first model, we introduce a robust multi-objective, multi-product, multi-echelon, multi-cycle, multi-capacity, green closed-loop supply-chain network under hybrid uncertainty with the objective of reducing costs, reducing environmental impacts, and increasing the social responsibilities and the reliability of the network. Second, we study the impact of tariffs and government regulations on the profitability of the network. Third, we evaluate the impact of using sensor embedded tires on the design of CLSC network. The analysis is done using a novel Robust Fuzzy/ Possibilistic Stochastics Programming (RFSP) model that controls scenario-based uncertainty (disruption risks) and fuzzy-based uncertainty (operational risks) in the network simultaneously and provides more reliable results for the managers and the decision makers. We evaluate the possibility and feasibility of expanding the existing forward logistic network at different capacity levels to cope with the market demand under various scenarios as well as the feasibility of establishing a new reverse logistic network at different capacity levels to cope with the return rate of EOL tires. A case example is considered to illustrate the implementations and validation of the proposed models. --Author's abstract

A tabu search based algorithm for the optimal design of multi-objective multi-product supply chain networks

Designing sustainable supply chain networks under uncertain environments: Fuzzy multi-objective programming

Managing the trade-offs between financial performance and credit solvency in the optimal design of supply chain networks under economic uncertainty

Integration of sale and leaseback in the optimal design of supply chain networks

The aim of this paper is to propose a robust reliable bi-objective supply chain network design (SCND) model that is capable of controlling different kinds of uncertainties, concurrently. In this regard, stochastic bi-level scenario based programming approach which is used to model various scenarios related to strike of disruptions. The well-known method helps to overcome adverse effects of disruptions and extend a network that is less vulnerable regarding disruptions strike. Also, scenario-based modeling approach enables decision makers (DMs) to the model uncertainty of model parameters regarding different scenarios that are disregarded in reliable SCND research scope. An effective robust programming method is employed to control the risk-aversion level of output decisions that helps company managers to adjust long-term effects of their decisions via determining uncertainty level of model parameters. Notably, extended bi-objective programming model minimizes total costs of network design aside with maximization of responsiveness of supply chain network. Agile and fast performing networks could be regarded as a long-term competitive advantage for companies that are modeled in the extended form as a different objective besides cost minimization. Finally, the extended robust reliable network model is implemented and evaluated based on real case study of a national project and output results demonstrates efficiency and applicability of proposed reliable network.

This case study deals with the design of reverse and forward supply chain network for an automobile battery manufacturer. Most research in this field has focused on independent reverse network designs and centralised collection network design for the returned old products. The case study reported in this paper seeks to contribute by experimenting with two different configuration networks for the distribution and collection of products. This facility location problem was solved by mixed-integer linear programming modelling tools. It is demonstrated that bypassing certain stage of supply chain network in the reverse flow can reduce the cost of the network and it also reduces the amount of time spent by products in the supply chain network. This study also brought out issues like de-centralised network, manufacturer's dilemma in managerial control over the collection, disturbance to existing network, time pressure with respect to reverse flow and integral design issues.

Supply chain networks change continuously due to varying objectives, requirements as well as restrictions. The ability of supply chain networks to adapt to changing requirements, especially in fast moving industries, is decisive. As sustainability issues in supply chain management are increasingly concerned among companies, adequate approaches for redesign and replanning considering sustainability become essential. This paper proposes a fuzzy-based approach to support the dynamic design and planning of sustainable supply chain networks from a stakeholder's perspective. An approach is introduced to define and select sustainability measures. In addition, a continuous monitoring of stakeholder requirements, supply chain performance and market trends accounts for the necessity of redesign and replanning. The approach will qualify companies to select sustainability measures to handle rising complexity within sustainable supply chain decision-making context. The findings contribute to the literature on stakeholder management within sustainable supply chain management (SSCM) research.

This article proposes a novel methodology for multistage, multiproduct, multi-item, and closed-loop Supply Chain Network (SCN) design under uncertainty. The method considers that multiple products are manufactured by the SCN, each composed by multiple items, and that some of the sold products may require repair, refurbishing, or remanufacturing activities. We solve the two main decisions that take place in the medium-/short-term planning horizon, namely partners’ selection and allocation of the received orders among them. The partners’ selection problem is solved by a cross-efficiency fuzzy Data Envelopment Analysis technique, which allows evaluating the efficiency of each SCN member and ranking them against multiple conflicting objectives under uncertain data on their performance. Then, according to the estimated customers’ demand, the order allocation problem is solved by a fuzzy bargaining game problem, where each SCN actor behaves to simultaneously maximize both its own profit and the service level of the overall SCN in terms of efficiency, costs, and lead time. An illustrative example from the literature is finally presented. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —We present a decision tool to address the optimal design, performance evaluation, and continuous improvement of modern cooperative SCNs. We propose an effective method to jointly solve the members’ selection and the orders’ allocation, considering the complex structure of modern SCNs, the multiobjective nature of the problems, and the uncertainty characterizing economic markets. Competition within SCNs stages and cooperation along the chain are considered, with the aim to improve both financial and environmental sustainability, while ensuring the highest service levels to customers.

Optimal supply chain network design with process network and BOM under uncertainties: A case study in toothbrush industry

Risk assessment and management for supply chain networks: A case study