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Supply chain management has gained much interest from researchers and practitioners in recent years. Proposing practical models that efficiently address different aspects of the supply chain is a difficult challenge. This research investigates an integrated production-distribution supply chain problem. The developed model incorporates parties with a specified number of processes to obtain raw materials from the suppliers in order to convert them to semi and final products. These products are then distributed through warehouses to end-distributors having uncertain demands. This uncertainty is captured as a dynamic stochastic data process during the planning horizon and is modeled into a... 

Integrated supplier selection and order allocation is a complex problem that is important for both designing and operating supply chains. It becomes especially complicated when quantity discounts are considered at the same time. Under such circumstances, most studies often formulate the problem as a Multi-Objective Linear Programming problem (MOLP), and then transform it to a Mixed Integer Programming problem (MIP) to handle the inherited multi-objectives, simultaneously. But, objectives are not of equal importance and in this approach scaling and subjective weighting often are not considered. In addition, some of the studies that use weighting method to solve the MOLP, usually ignore to... 

Decentralized supply chain management is found to be significantly relevant in today’s competitive markets. Production and distribution planning is posed as an important optimization problem in supply chain networks. Here, we propose a multi-period decentralized supply chain network model with uncertainty. The imprecision related to uncertain parameters like demand and price of the final product is appropriated with stochastic and fuzzy numbers. We provide mathematical formulation of the problem as a bi-level mixed integer linear programming model. Due to problem’s convolution, a structure to solve is developed that incorporates a novel heuristic algorithm based on Kth-best algorithm, fuzzy... 

In this article, we design a revenue-sharing contract to coordinate inventory control decisions in a serial supply chain consisting of one supplier, one vendor, and one retailer. We assume that the retailer faces Poisson demand and his unsatisfied demands will be lost. The retailer applies one-for-one period policy in which he constantly places an order for one unit of product to the vendor in a predetermined time interval which results in a deterministic demand for the vendor. Vendor orders the required quantity from supplier which will be immediately received at the vendor’s warehouse. Solution procedures are developed to find the equilibrium in the vendor managed inventory program with a... 

In this paper, we design a revenue sharing contract to coordinate pricing and inventory control decisions in a serial supply chain consisting of one supplier, one manufacturer and one retailer. We assume that the retailer faces Poisson demand and his unsatisfied demands will be lost. The retailer applies one-for-one period policy in which he constantly places an order for one unit of product to the manufacturer in a predetermined time interval which results in a deterministic demand for the manufacturer. Solution procedures are developed to find the equilibrium in the Vendor Managed Inventory (VMI) program with a revenue sharing contract, in which no party is willing to deviate from for the... 

As a competitive advantage in modern organizations, product diversification may cause complexities in today's extended supply chains. However, the Common Platform (CP) Strategy, as a concept of gaining maximum variety by minimum production elements, is believed to be one of the answers to eliminate or decrease these complexities. The main purpose of this paper is to provide a simulation framework for modeling the supply network of a case study in automotive industry in order to study the impacts of part commonality through the chain. The electrical wiring harness is selected as the main part to be studied according to essentiality and challenges of its procurement for the production of cars... 

Increasing rates of environmental and social concerns involved in various communities have recently attracted researchers’ attention to consider them in proper designs of sustainable supply chains (SSCs). In this paper, the planning problem of a multi-period multi-echelon sustainable closed loop supply chain (SCLSC) is investigated. A comprehensive model that seriously takes into account the social and environmental aspects of the supply chain (SC) decisions and measures their social and environmental effects using the GRI (Global Reporting Initiative) guideline indicators is proposed. The proposed planning model includes tactical decisions comprising the price of the product and logistic... 

The growing rate of population and technological advancement have led to an increase in natural resource consumption, which has caused irreparable damage to the environment. The implementation of green supply chain management is one of the most effective ways to deal with environmental degradation. Therefore, in this paper, a bi-objective mixed integer linear programming model is developed to design a green supply chain network. In the proposed model, the possibility of customer storage, being faced with shortage, locating of distribution centres, green vehicle routing problem, split delivery, multi-depot vehicle routing problem (VRP), capacitated VRP, and uncertainty in demands will be... 

Food, energy, and water (FEW) resources have high interconnection and interdependencies as each resource can be affected by the other two. Thus, the Nexus approach is introduced and implemented to manage FEW. This chapter discusses each sector of FEW: availability, production, consumption, interaction, and interconnection between them, and finally suggests some action to improve the operation of the Nexus. © Springer Nature Switzerland AG 2020  

Green products are increasingly considered by companies, owing to the significant attention of government regulations, customers’ requests and competitors. Here, we deal with Green Product Families (GPFs) by selecting green components, modules and products which are produced based on the assembling to order (ATO) approach to cover diverse customer needs. Designing a GPFs is important but not sufficient for sustainable optimization. In fact, we need to simultaneously consider the supply chain of a GPF to control the pollution generated in the downstream supply chain. For a sustainable optimization approach, this joint configuration is usually structured based on economic, environmental and... 

Supplier selection and order allocation are important keys for reverse logistics and closed-loop supply chain networks especially with the presence of demand–supply imbalance risks. If such uncertainties and risks are not foreseen in the chain, and corresponding appropriate measures are not taken to handle them, irreparable damages would be expected consequently. The importance of this issue in closed-loop supply chains is more appreciated due to the importance and the effect of this chain on the environment. In this research, the disruption risk and the uncertainties related to the demand, market price, and the number of returned products are simultaneously considered. Purchasing from the... 

This paper considers a two-level supply chain consisting of one warehouse and one retailer. Unlike the most similar models which determine the optimal ordering policy according to inventory cost only, in this model, we also consider the transportation cost. We assume that the demand rate at the retailer is known and the demand is confined to a single item. Shortages are allowed neither at the retailer nor at the warehouse. The objective is to find the economic order quantities for both the retailer and the warehouse which minimize the total cost. That is. the sum of the holding and ordering cost at the retailer and warehouse as well as the transportation cost from warehouse to retailer.... 

In this paper, we design and optimise an integrated four-level Supply Chain (SC), which contains a supplier, a producer, a wholesaler and multiple retailers. The levels cooperate to make an Integrated SC (ISC) so that the inventory cost is minimised and the reliability is maximised, simultaneously. The model is constrained by real stochastic constraints on total space, number of orders, procurement cost, shortage cost, setup cost and production capacity. An Lp-Metric function converts the reliability function and cost function into a single-objective function to optimise the number of stockpiles and period lengths. The designed ISC is a large-scale Nonlinear Programming (NLP) and hard to... 

This study explores a Robust, Risk-aware, Resilient, and Sustainable Closed-Loop Supply Chain Network Design (3RSCLSCND) to tackle demand fluctuation like COVID-19 pandemic. A two-stage robust stochastic multiobjective programming model serves to express the proposed problems in formulae. The objective functions include minimising costs, CO2 emissions, energy consumption, and maximising employment by applying Conditional Value at Risk (CVaR) to achieve reliability through risk reduction. The Entropic Value at Risk (EVaR) and Minimax method are used to compare with the proposed model. We utilise the Lp-Metric method to solve the multiobjective problem. Since this model is complex, the... 

This research develops a humanitarian cold supply chain model with equity consideration for COVID-19 vaccine distribution during a pandemic, considering deprivation cost and an important social concept named equity. The proposed comprehensive plan minimizes all incurred costs, including transportation costs, shortage costs, deprivation costs, and holding costs, while aiming at eliminating infection and mortality rates. The proposed three-echelon supply chain model includes suppliers, distributors, and affected regions (ARs), as destinations. We apply the proposed model to the actual vaccine distribution data during the COVID-19 outbreak in Europe. A mixed integer programming (MIP) model is... 

The vast nationwide COVID-19 vaccination programs are implemented in many countries worldwide. Mass vaccination is causing a rapid increase in infectious and non-infectious vaccine wastes, potentially posing a severe threat if there is no well-organized management plan. This paper develops a mixed-integer mathematical programming model to design a COVID-19 vaccine waste reverse supply chain (CVWRSC) for the first time. The presented problem is based on minimizing the system's total cost and carbon emission. The uncertainty in the tendency rate of vaccination is considered, and a robust optimization approach is used to deal with it, where an interactive fuzzy approach converts the model into... 

Demand forecasting has always been a concern for business owners as one of the main activities in supply chain management. Unlike the past, that forecasting was done with the help of a limited amount of information, today, using advanced technologies and data analytics, forecasting is performed with machine learning algorithms and data-driven methods. Patterns and trends of demand, customer information, preferences, suggestions, and post-consumption feedbacks are some types of data that are used in various demand forecasting efforts. Traditional statistical methods and techniques are biased in demand prediction and are not accurate; so, machine learning algorithms as more popular techniques... 

In this paper, a mathematical model is proposed to assess the flow distribution based on the traffic criterion. In the mathematical model, the resilience and stability criteria are developed based on the concepts of control engineering and optimal control. The results show that the route stability is dependent on the traffic parameter. Then, considering several factors including stability, safety, resilience, risk-averse investment, the environment and noise, a decision-making model is presented to evaluate the performance of the flow distribution routes during crises. Goal programming and data-oriented modelling are used to solve the mathematical model. Data envelopment analysis (DEA) is... 

The null-space method (NSM) for solving the nonlinear programming (NLP) is used to transform an indefinite system into a symmetric positive definite one of a smaller dimension. In this paper, an NSM optimises the constrained NLP model of the inventories in multi-level supply chains (SCs). The presented NSM can give a direct method with a predictable level of fill without pivoting, decreasing the number of taken iterations to find the optimum solution. We transform the nonlinear equations into an NLP model, which NSM can solved. We also investigate the suitability of using null-space-based factorisations to derive sparse direct methods. Accordingly, an integrated lot-sizing model of the... 

This research aims at determining the main criteria of the green supply chain management (GSCM) and providing a framework to assess and compare the greenness of dairy industries. There has been a research gap in evaluating the greenness of this industry in Iran to be bridged. In the first phase, through studying literature and acquiring academics and experts’ opinions, the framework is classified into 8 criteria and 32 sub-criteria as enablers and relevant to the GSCM, considered as base subjects in preparing questionnaires. The second phase uses experts' opinions and through the Fuzzy Delphi method, 26 sub-criteria are screened, confirmed, and employed. Also, the cause-and-effect criteria...