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    A decision support framework to evaluate the sustainability performance of urban road transportation
    (Springer Heidelberg, 2023) Babaei, Ardavan; Khedmati, Majid; Jokar, Mohammad Reza Akbari; Tirkolaee, Erfan Babaee
    This study proposes a decision support framework (DSF) based on two data envelopment analysis (DEA) models in order to evaluate the urban road transportation of countries for sustainable performance management during different years. The first model considers different years independently while the second model, which is a type of network model, takes into account all the years integrated. A multi-objective programming model under two types of uncertainties is then developed to solve the proposed DEA models based on a revised multi-choice goal programming (GP) approach. The efficiency scores are measured based on the data related to several major European countries and the factors including the level of freight and passenger transportation, level of greenhouse gas emissions, level of energy consumption, and road accidents which are addressed as the main evaluation factors. Eventually, the two proposed models are compared in terms of interpretation and final achievements. The results reveal that the efficiency scores of countries are different under deterministic/uncertain conditions and according to the structure of the evaluation model. Furthermore, efficiency changes are not necessarily the same as productivity changes. The high interpretability (up to 99.6%) of the models demonstrates the reliability of DSF for decision-making stakeholders in the transport sector. Furthermore, a set of managerial analyses is conducted based on different parameters of the performance evaluation measures for these countries including the productivity changes during the period under consideration, resilience of the countries, detection of the benchmark countries, ranking of different countries, and detection of the patterns for improving the transportation system.
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    Designing an integrated blockchain-enabled supply chain network under uncertainty
    (Nature Portfolio, 2023) Babaei, Ardavan; Khedmati, Majid; Jokar, Mohammad Reza Akbari; Tirkolaee, Erfan Babaee
    With the development of communication infrastructure, the design of supply chains has changed significantly. Blockchain technology, as one of the most cutting-edge technologies, can promote transparency among members of the supply chain network. To the best of our knowledge, this is the first study that tries to develop a novel bi-objective optimization model to integrate the transparency resulting from the use of blockchain for designing a three-level supply chain network. The first objective function is to minimize total cost while the second objective function seeks to maximize transparency based on the application of blockchain technology. Moreover, it is worth noting that it is the first attempt to investigate the role of a blockchain model under stochastic conditions. The bi-objectiveness and stochastic nature of the proposed model are then treated using Fuzzy Goal Programming (FGP) and Chance-Constrained programming (CCP) approaches, respectively. To tackle the problem, an improved Branch and Efficiency (B&E) algorithm is developed by incorporating transparency along with cost and service. The impacts of blockchain exclusively through transparency (Case 1) or through transparency, cost, and benefits (Case 2) in Supply Chain Design (SCD) are compared. The results demonstrated that the first case has less computational complexity and better scalability, while the second case has more transparency, less congestion, and more security. As one of the main implications, supply chain managers who are focused on cost minimization as well as transparency maximization are advised to take into account the trade-off between featuring costs and benefits of blockchain technology.
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    Innovative supply chain network design with two-step authentication and environmentally-friendly blockchain technology
    (Springer, 2024) Babaei, Ardavan; Tirkolaee, Erfan Babaee; Ali, Sadia Samar
    Blockchain Technology (BT) has the potential to revolutionize supply chain management by providing transparency, but it also poses significant environmental and security challenges. BT consumes energy and emits carbon gases, affecting its adoption in Supply Chains (SCs). The substantial energy demand of blockchain networks contributes to carbon emissions and sustainability risks. Moreover, for secure and reliable transactions, mutual authentication needs to be established to address security concerns raised by SC managers. This paper proposes a tri-objective optimization model for the simultaneous design of the SC-BT network, considering a two-step authentication process. The model considers transparency caused by BT members, emissions of BT, and costs related to BT and SC design. It also takes into account uncertainty conditions for participating BT members in the SC and the range of transparency, cost, and emission targets. To solve the model, a Branch and Efficiency (B&E) algorithm equipped with BT-related criteria is developed. The algorithm is implemented in a three-level SC and produces cost-effective and environmentally friendly outcomes. However, the adoption of BT in the SC can be costly and harmful to the environment under uncertain conditions. It is worth mentioning that implementing the proposed algorithm from our article in a three-level SC case study can result in a significant cost reduction of over 16% and an emission reduction of over 13%. The iterative nature of this algorithm plays a vital role in achieving these positive outcomes.
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    An integrated decision support system to achieve sustainable development in transportation routes with traffic flow
    (Springer Heidelberg, 2023) Babaei, Ardavan; Khedmati, Majid; Jokar, Mohammad Reza Akbari; Tirkolaee, Erfan Babaee
    Due to the growing population and demand, transportation planning has received special importance in the context of supply chain management. One of the major challenges in transportation planning is the traffic problem. This challenge affects the safety, environmental, and efficiency factors of transportation systems. Accordingly, in this study, the routes, which are important pillars of transportation planning, are examined from the perspective of sustainability. In this regard, a novel decision support system is developed, wherein at first, some decision-making methods including Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), entropy technique, Nash equilibrium point (NEP), and data envelopment analysis (DEA) are employed to analyze and determine unstable routes. Then, a bi-level leader-follower multi-objective optimization model is developed, based on the vehicle types, to evaluate the routes at different time intervals and identify the most efficient time intervals as a traffic pattern. Finally, the proposed models are implemented in a real case study based on the freeways in Tehran. According to the main finding, it is revealed that heavier and bulkier vehicles have a greater impact on road instability.
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    Performance evaluation of omni-channel distribution network configurations considering green and transparent criteria under uncertainty
    (MDPI, 2022) Babaei, Ardavan; Khedmati, Majid; Jokar, Mohammad Reza Akbari; Tirkolaee, Erfan Babaee
    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, and environmental criteria; and then, forms a consensus on the evaluation results generated according to different criteria by utilizing an uncertain optimization model. To the best of our knowledge, this is the first attempt in which such an algorithm has been employed to take into account the mentioned criteria in a model to evaluate OCDNCs. The application of the proposed models was investigated in a case study in relation to the Indian retail industry. The results show that the configuration with the most connections among its members was the most stable, robust, and efficient.
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    Sustainable transportation planning considering traffic congestion and uncertain conditions
    (Pergamon-Elsevier Science Ltd, 2023) Babaei, Ardavan; Khedmati, Majid; Jokar, Mohammad Reza Akbari; Tirkolaee, Erfan Babaee
    Transportation activities, especially road transportation, have a great impact on economic growth. On the other hand, sustainability is a major concern for transportation planning. In this work, a data-oriented network is developed to evaluate the sustainability of vehicle types. Then, this network is integrated with a multi-objective optimization model in order to provide the planning of a three-stage transportation problem, according to traffic congestion. Some criteria including total profit, efficiency of different vehicle types, relationship among the customers supplied by a specified retailer, risk of underestimating unmet demand, and selling price are used to determine the objective functions. The Chance-Constrained Programming (CCP) and Chebyshev Goal Pro-gramming (CGP) approaches are applied to solve the proposed integrated model. To the best of the authors' knowledge, it is the first time that traffic congestion under the conditions of simultaneous fuzzy and stochastic uncertainty has been integrated into sustainable transportation planning. In addition, the applicability and validity of the developed model are assessed on a case study. The results are then analyzed and appraised by Data Envelopment Analysis (DEA) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods. The findings prove that the components of the proposed model have a very beneficial effect on the solution, and also perform much better than the competing approaches in the literature. Two important points from the results of this paper are that (a) traffic congestion is more effective in the initial levels of the supply chain, and (b) transportation planning using efficient vehicles may reduce the desirability of the objective function values.