Efficient and sustainable closed-loop supply chain network design: A two-stage stochastic formulation with a hybrid solution methodology
طراحی شبکه زنجیره تامین حلقه بسته کارآمد و پایدار: یک فرمول تصادفی دو مرحله ای با روش راه حل ترکیبی-2021
In recent years, consumers and legislators have pushed companies to design their supply chain networks to consider environmental and social impacts as an important performance outcome. Due to the role of resource utilization as a key component of logistics network design, another primary goal of design is ensuring available scarce resources are used as efficiently as possible across all facilities. To address efficiency issues in a sustainable closed-loop supply chain network, a stochastic integrated multi-objective mixed integer nonlinear programming model is developed in this paper, in which sustainability outcomes as well as efficiency of facility resource utilization are considered in the design of a sustainable supply chain network. In doing so, efficiency is assessed using a bi-objective output-oriented data envelopment analysis model. A hybrid three-step solution methodology is presented that creates a linear form of the original mixed integer nonlinear programming problem using piecewise McCormick envelopes approach. In the second step, an aggregated single objective programming model is derived by exploiting the multi-choice goal programming. Finally, a Lagrangian relaxation algorithm is developed to effectively solve the latter stochastic single objective mixed integer linear programming problem. The application of the proposed approach is investigated with data drawn from a case study in the electronics industry. This case study illustrates how firms may balance sustainability and efficiency in the supply chain network design problem. Further, it demonstrates the integration of efficiency results in improving economic aspects of sustainability as well as social responsibility outcomes, but also highlights the trade-offs that exist between efficiency and environmental impacts.
Keywords: Closed-loop supply chain network | Sustainability | Data envelopment analysis | Stochastic programming | Multi-choice goal programming | Lagrangian relaxation
A multi-objective fuzzy robust stochastic model for designing a sustainable-resilient-responsive supply chain network
یک مدل تصادفی محکم فازی چند هدفه برای طراحی یک شبکه زنجیره تأمین پایدار ، قابل انعطاف و پاسخگو-2021
This study proposes a multi-objective mixed-integer programming model to configure a sustainable supply chain network while considering resilience and responsiveness measures. The model aims at minimizing the total costs and environmental damages while maximizing the social impacts, as well as the responsiveness and resilience levels of the supply chain network. An improved version of the fuzzy robust stochastic optimization approach is proposed to tackle the uncertain data arising in the dynamic business environment. Furthermore, a new version of meta-goal programming named the multi-choice meta-goal programming associated with a utility function is developed to solve the resulting multi-objective model. A case study in the water heater industry is investigated to illustrate the application of the proposed model and its solution approach. The numerical results validate the proposed model and the developed solution method. Finally, interactions between the sustainability, responsiveness, and resilience dimensions are investigated and several sensitivity analyses are performed on critical parameters by which useful managerial insights are provided.
Keywords: Supply chain network design | Sustainability | Resilience | Responsiveness | Fuzzy robust stochastic optimization | Multi-choice meta-goal programming
Two-echelon supply chain network design with trade credit
Two-echelon supply chain network design with trade credit-2021
This study considers a two-echelon supply chain that is comprised of an outside vendor, multiple distribution centers (DCs), and multiple retailers. The retailers have access to trade credit offered by upstream suppliers. We propose an integrated DC-retailer network design model that optimizes trade credit terms and safety stock levels, in addition to the decisions of DC locations, DC-retailer assignments, and inventory replenishment policies typically considered in the literature. The operating and handling cost is concave and non-decreasing to capture economies of scale whereas most existing studies simply assume that such cost is linear in demand. Trade credit financing cost is characterized in a way that preserves the important mathematical structure of the classic warehouse retailer network design model. Leveraging on the sub modularity property of the cost components, we developed a polymatroid cutting-plane solution algorithm, which is effective for practically sized problem in- stances in numerical experiments. The results show that incorporating trade credit financing into supply chain network design may substantially reduce the total cost. Further, our study suggests a more consolidated supply chain network when either the safety stock or financing cost increases. Interestingly, as financing cost rises, a high-volume and low-frequency reorder pattern is favored, but the opposite is recommended when financing gain increases. The variation of each individual cost component is also analyzed for an in-depth understanding of the impact of operational and financial parameters on supply chain optimization.
Keywords: Network design | OWMR system | Multi-echelon inventory management | Trade credit | Polymatroid cutting plane
Multi-period multi-product closed loop supply chain network design: A relaxation approach
طراحی شبکه زنجیره تامین حلقه بسته چند محصولی چند دوره ای: یک رویکرد آرام سازی-2021
Growing concern about environmental deterioration, manifested in new laws to protect the environment and business competition, has stimulated the idea of Closed Loop Supply Chains (CLSC). This paper develops strategic decision-making models for two different CLSCs with multiple products over multiple periods. One of the net- works has six levels, while the other has four levels, and they can be applied to products with different levels of complexity during inspection and remanufacturing operations. The supply chain networks are modeled as Integer Linear Programs (ILP) designed to assist decision-making in terms of location/allocation, transportation, and inventory. Taking advantage of the properties of the formulations, we propose an integer relaxation approach to obtain the optimal solution to ILP. The proposed models and methodologies are illustrated with case studies from the literature and with hypothetical datasets. This research contributes with design standard con- figurations for CLSCs that can be used for different types of products. Directly using these configurations is advantageous because the models proposed can be quickly solved using the integer relaxation approach. The associated trials confirm the utility of the models for the case studies and demonstrate encouraging results for the hypothetical datasets.
Keywords: Logistics | Production | Integer Linear Program | Closed Loop Supply Chains | Multi-period model
A hybrid modeling approach for green and sustainable closed-loop supply chain considering price, advertisement and uncertain demands
یک روش مدل سازی ترکیبی برای زنجیره تامین حلقه بسته سبز و پایدار با در نظر گرفتن قیمت ، تبلیغات و تقاضاهای نامشخص-2021
The closed-loop supply chain network design (CLSCND) has garnered a lot of attention since it can handle economic and environmental issues. Likewise, supply chain coordination (SCC) tools can play an important role in enhancing the performance of the supply chains. This paper proposes a new hybrid method, in which SCC decisions and CLSCND objectives are simultaneously involved. First, this approach makes price, greenness, and advertisement decisions, and then it aims at maximizing profit and minimizing CO2 emission. A new nonlinear programming (NLP) model is developed based on the sensitivity of the return rate to green quality and the customers’ maximum tolerance, while the demands are uncertain. In order to overcome the uncertain demands, a robust optimization (RO) model is used. A Lagrangian relaxation algorithm is also employed to solve large-scale instances in a logical running time. The applicability of the proposed approach is corroborated through several examples. The results indicate an improvement in the performance of economic and environmental objectives under greening and advertising decisions. Furthermore, the proposed RO model outperforms the model that does not consider a robust approach.
Keywords: Closed-loop supply chain | Supply chain coordination | Supply chain network design | Robust optimization | Lagrangian relaxation | Uncertain demand
Resilience cloud-based global supply chain network design under uncertainty: Resource-based approach
انعطاف پذیری مبتنی بر ابر طراحی شبکه جهانی زنجیره تامین تحت عدم اطمینان: رویکرد مبتنی بر منابع-2021
This study presents a fuzzy multi-objective mathematical programming model to design an efficient and resil- ience global supply chain network structure based on the service-oriented approach. Service composition and transportation within globally scattered resources are considered under the cloud manufacturing paradigm. The proposed comprehensive model is adapted to a global electrical medical device manufacturing system. Key performance measures include robustness, agility, leanness, and flexibility as resiliency pillars are considered in designing the network under uncertainty. To efficiently deal with the computational tractability of this non- linear and multi-objective optimization problem, a new hybrid solution algorithm is developed that in- corporates fuzzy multi-criteria decision-making methods and augmented ε-constraint method. Obtained computational results of a real case study present that the proposed service-oriented global supply chain network design can respond to its global customers’ demands in a resilient as well as efficient manner.
Keywords: Resilience supply chain | Cloud manufacturing | Resource-based approach | Uncertainty | Multi-objective
A Capacity Planning Approach for Sustainable-Resilient Supply Chain Network Design under Uncertainty: A Case Study of Vaccine Supply Chain
رویکرد برنامه ریزی ظرفیت برای طراحی شبکه زنجیره تأمین پایدار و قابل انعطاف تحت عدم قطعیت: مطالعه موردی زنجیره تأمین واکسن-2021
This paper introduces a multi-objective mathematical model to design a sustainable resilient supply chain based on strategic and tactical decision levels. The resolution is to proactively plan for an optimal configuration to satisfy customer demands when the firm is highly vulnerable to operational and disruption risks. Compared to previous studies, we take the application of capacity planning in terms of redundancy to design a supply chain network that is resilient toward the demand-side by an optimization framework. A real-world influenza vaccine supply chain is studied to validate the proposed model and examine the tradeoff between resilience and sustainability. A robust fuzzy optimization approach is employed to cope with uncertainties. Then, the multi-objective model is solved by applying multi-choice goal programming with a utility function approach. Accordingly, managerial insights are suggested by analyzing the effects of structural parameters on the quantitative results. It is revealed that having redundancies in the supply chain does not always increase the total costs.
Keywords: Supply Chain Network Design | Sustainability | Resiliency | Robust Fuzzy Optimization | Multi Choice Goal Programming with Utility Function.
Supply Chain Network Design Considering Customer Psychological Behavior-A 4PL Perspective
طراحی شبکه زنجیره تأمین با در نظر گرفتن رفتار روانشناختی مشتری-دیدگاه 4PL-2021
From the perspective of Fourth Party Logistics, a novel supply chain network design problem considering customer psychological behavior is proposed in this paper. First, we calculate the minimum cost of the supply chain network design in Fourth Party Logistics when the demand of customers is fully satisfied. In the shortage of the investment in the process of supply chain network design, the demand of customers can be partially satisfied. Then, customer psychological behavior is considered to maximize the value function of customer satisfaction under cost constraint. After introducing the definitions of the psychological reference point and the service level for customers based on the prospect theory, we formulate a non-linear integer programming model for Fourth Party Logistics network design problem. Since the objective function of the proposed model is non-linear, an approximation linearization method is introduced to adjust the proposed model to be an equivalent linear model. Numerical experiments are designed to justify the effectiveness of the proposed method. Through a thorough analysis on customer psychological behavior, it can be seen that customers tend to be more risk-averse for gains than risk-seeking for losses in Fourth Party Logistics supply chain network design. Moreover, valuable investment insights are recapitulated. This proposed method provides an effective tool for a Fourth Party Logistics provider to give reasonable suggestions to an investor in Fourth Party Logistics supply chain network design. Furthermore, we extended the basic model of 4PL supply chain network design considering customer satisfaction with multiple commodities and provided a solution method based on greedy adding heuristic to further reduce the calculation time for large scale cases.
Key words: Fourth Party Logistics | Supply Chain Network Design | Psychological Behavior | Customer Satisfaction | Approximation Linearization
Costs of resilience and disruptions in supply chain network design models: A review and future research directions
هزینه های انعطاف پذیری و اختلالات در مدل های طراحی شبکه زنجیره تامین: یک مرور و دستورالعمل های آینده تحقیق-2021
Supply chain network design (SCND) is a key strategic decision in supply chain management (SCM). One particular area of SCND is concerned with disruption risk modelling. This paper presents a systematic literature review of quantitative models of SCND under disruption risks in industrial SCM and logistics. More specifically, our analysis is focused on different costs induced by the planning of proactive investments in robustness and through parametrical/structural adaptation at the recovery stage. This review can be of value for researchers and decision-makers alike for several reasons. First, we categorise the existing knowledge based on decision-making problems, which can be instructive for a convenient association of a particular SCND problem to a modelling domain according to network-wise, supply-side and demand-side perspectives. Second, our analysis focuses on the costs specifically induced by disruption risks and resilience investments. Third, we offer a dedicated section related to disruption probability formulation methods and their impact on resilience costs. Fourth, the integration of different SCM dimensions (i.e., social impact, environmental impact, responsiveness, and risk- aversion) and the associated multi-objective modelling settings are discussed along with disruption risks in SCND models. Finally, we summarize our findings as insights from a managerial perspective. Drawbacks and missing aspects in the related literature are highlighted, and we lay out several research directions and open questions for future research.
Keywords: Supply chain network design | Facility location | Disruption risk | Resilience cost | Ripple effect | Covid-19
Unpacking the role of primary packaging material in designing green supply chains: An integrated approach
Unpacking the role of primary packaging material in designing green supply chains: An integrated approach-2021
Due to the adverse impact of packaging materials on several ecosystems, the circular and sustainable approaches to manage packaging waste have been receiving increasing attention worldwide. Plastic pails are widely used primary packaging materials that are cost-effective, lightweight, yet long-lasting. In the present study, we pro- pose a closed-loop supply chain (CLSC) network design model to jointly optimize the decisions related to the location of collection, sorting, and recycling centers, and the quantity of plastic pales to be recycled and/or freshly produced and distributed. The proposed model is augmented with an incentive mechanism to acquire used plastic pails from customers as well as a green supplier selection procedure. In addition to the traditional objective of profit maximization, the proposed model also minimizes carbon emission, maximizes the return of used plastic pails, and prioritize suppliers for the procurement of sustainable packaging raw materials. A set of non-dominated solutions to the proposed multi-objective model are obtained using the Augmented ε-constraint method (AUGMECON). The results of AUGMECON are also compared with other methods such as weighted sum method and Augmented Tchebycheff method. It is oberseved that AUGMECON produces diverse set of pareto- optimal solutions for the considered problem. The applicability of the model is explained using an illustrative example of an adhesive manufacturer in India. Further, several managerial insights are drawn by carrying out sensitivity analysis through scenario building.
Keywords: Primary packaging | Closed-loop supply chain network design | Incentives | Supplier selection | Multi-objective optimization | Augmented ε-constraint method