Sharif Digital Repository

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... 

Satisfying customer demand is one of the growing concerns of supply chain managers. On the other hand, the development of internet communications has increased online demand. In addition, the COVID-19 pandemic has increased the demand for online shopping. One of the useful concepts that help to address this concern is the omni-channel strategy, which integrates online and traditional channels with the aim of improving customer service level. For this purpose, this paper proposes an algorithm for evaluating Omni-channel Distribution Network Configurations (OCDNCs). The algorithm applies an extended Data Envelopment Analysis (DEA) model to evaluate OCDNCs based on cost, service, transparency,... 

This paper addresses a bi-level mixed-integer nonlinear programming (MINLP) model for the competitive facility location problem in a closed-loop supply chain (CLSC), in which a firm (i.e., leader) aims at entering a market by locating new distribution and collection facilities, where a competitor (i.e., follower) already exists. The goal is to find the location and attractiveness of each facility going to be established by the leader who seeks to maximize its profit while also taking the follower's response into account. The attractiveness of each facility is a function of integer variables related to the facility's characteristics. Customer behavior is considered to be probabilistic based... 

The viable closed-loop supply chain network (VCLSCND) is a new concept that integrates sustainability, resiliency, and agility into a circular economy. We suggest a hybrid robust stochastic optimization by minimizing the weighted expected, maximum, and entropic value at risk (EVaR) of the cost function for this problem. This form considers robustness against demand disruption. Finally, CLSC components are located, and quantity flows are determined in the automotive industry. The results show that the VCLSCND cost is less than not considering viability and has a − 0.44% gap. We analyze essential parameters. By increasing the conservative coefficient, confidence level, and the scale of the... 

Supply chain management integrates planning and controlling of materials, information, and finances in a process which begins from suppliers and ends with customers. Optimal planning decisions made in such a distribution network usually include transportation, facilities location, and inventory. This study presents a new approach for considering customers’ differentiation in an integrated location-allocation and inventory control model using transfer recurrent neural network (RNN). In this study, a location and allocation problem is integrated with inventory control decisions considering two classes of strategic and non-strategic customers. For the first time, a novel transfer RNN is applied... 

Supply Chain (SC) coordination, quality requirements, and environmental issues are the main areas of interest within the field of inventory management. Few studies have integrated these concepts into an inventory problem despite its overwhelming necessity. In this direction, this paper deals with a vendor-buyer SC under the Vendor-Managed Inventory with Consignment Stock (VMI-CS) agreement. According to the agreement, the vendor bears the buyer's financial holding cost in return for the storage of products in the buyer's warehouse. Further, each shipment involves a random fraction of repairable items, which need to be withdrawn from the inventory system. Unlike the existing literature, when... 

This paper studies a two-echelon reverse supply chain (RSC) involving a remanufacturer and a collector, in which the collector receives the used products by paying a reward to consumers. The reward amount given to customers is crucial for encouraging them to exchange used products. An exchanged item is accepted if it meets the minimum acceptable quality level (AQL). Both the remanufacturing capacity and the quality of exchanged products present uncertainties. Under the buyback contract, the remanufacturer purchases used products at a higher price than in the decentralized and centralized cases from the collector. In return, the collector undertakes to repurchase a certain number of used... 

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... 

The rapid growth in the supply chain of electronic devices has led companies to purchase Intellectual Property or Integrated Circuits from unreliable sources. This dispersion in the design to fabrication stages of IP/IC has led to new attacks called hardware Trojans. Hardware Trojans can bargain information, reduce performance, or cause failure. Various methods have been introduced to detect or prevent hardware Trojans. Machine learning methods are one of these. Selecting the type and number of input variables in the learning algorithm has an important role in the performance of the learning model. Some previous hardware Trojan detection studies have used structural gate-level features to... 

Supply chain management (SCM) deals with various strategic, tactical, and operational level decisions in which pricing is of utmost importance to decision makers. Most of the real-life supply chain pricing problems consider competition as a crucial factor in order to expand the market share and tackle emerging competitors. Accordingly, competitive pricing in SCM has attracted great attention by practitioners and academicians in the last four decades. Now after 40 years, it seems necessary to systematically review and classify the previous studies and present the most appealing future research directions. This paper provides a comprehensive review of the state-of-the-art published papers in... 

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... 

Reinforcing the correlation between Gas and Electricity Systems (G&ESs) susceptible to diverse factors ranging from anthropogenic climate change to the advent of new conversion/generation technologies has remarkably brought into focus the co-expansion of G&ESs using a new concept so-called Energy Hub (EH) as well as the potential of storage systems. To assess the effectiveness of EH approach and the role of storages in the coordinated plans of G&ES, this study proposes a comprehensive EH-based planning model for co-expansion of G&ES supply chains with respect to the role of Gas Storage Systems (GSSs). As a Mixed-Integer Linear Programming (MILP) problem, the model is applied to a real... 

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... 

With the advent of new technologies and globalization of business, supply chains have turned into indispensable tools for gaining competitive advantage. The application of new technologies like blockchain can benefit sustainable energy supply chains by improving chain and logistics operations in the areas of trust, transparency and accountability, cooperation, information sharing, financial exchanges, and supply chain integration. However, the efforts to adopt such technologies in supply chains tend to face many challenges and challenges, which can seriously threaten their success. Therefore, it is crucial to carefully examine the challenges to blockchain technology application. This... 

Many companies face challenges in reducing their supply chain costs while increasing sustainability and customer service levels. A comprehensive framework for a sustainable closed-loop supply chain (CLSC) network is a practical solution to these challenges. Hence, for the first time, this study considers an integrated multi-objective mixed-integer linear programming (MOMILP) model to design sustainable CLSC networks with cross-docking, location-inventory-routing, time window, supplier selection, order allocation, transportation modes with simultaneous pickup, and delivery under uncertainty. An intelligent simulation algorithm is proposed to produce CLSC network data with probabilistic... 

In the eld of supply chain, selecting a suitable green supplier could signi cantly help us decrease the cost and risks of the operations and increase the quality of green supply. This paper develops an integrated two-stage approach based on Fuzzy Analytic Hierarchy Process (FAHP) and multi-objective mixed-integer linear programming to select suppliers and allocate order in the green supply chain. In the rst stage, suppliers are evaluated using FAHP method and in the second stage, a multi-product multi-period supply chain is developed considering green location-routing problem, discounting, and time window under uncertainty. Then, a fuzzy solution approach is applied to solve the proposed... 

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... 

Here, a fuzzy multi-period multi-echelon multi-objective mixed-integer non-linear programming (MOMINLP) model is considered for a sustainable multi-product multi-site multi-distribution multi-customer supply chain in forward flow having multi-centers for collecting, checking, repairing and decomposing and multi-disposal centers in the reverse flow. Minimizing the total cost of the closed-loop supply chain (CLSC), elevating the customer satisfaction degrees, minimizing the total waiting time, minimizing the manufacturing site greenhouse gases and minimizing the CO2 emissions from vehicles are considered as the objective functions. Furthermore, integration of strategic decisions of flow...