Evaluation of Supply Chain of a Shipping Company in Iran by a Fuzzy Relational Network Data Envelopment Analysis Model

Omrani, Hashem; Keshavarz, Mehdi; Ghaderi, S.F.

doi:10.24200/sci.2017.4415

Cited by 4 publications

(4 citation statements)

References 35 publications

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“…Data envelopment analysis (DEA) is a widely used technique for performance evaluation in supply chain management and supply chain planning.Furthermore, the DEA technique has many applications in the field of sustainability (Hermoso-Orzaez et al 2020;Jiang et al 2021;Ebrahimi et al 2021;Omrani et al 2018;Aydin & Tirkolaee 2022). By mathematical programming, DEA measures the relative efficiency of peer decision-making units (DMUs) for producing the maximum output or using the minimum input where each DMU has some inputs and outputs.…”

Section: Literature Reviewmentioning

confidence: 99%

A branch and efficiency algorithm to design a sustainable two-echelon supply chain network considering traffic congestion and uncertainty

Babaei

Khedmati

Jokar

2022

Environ Sci Pollut Res

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This work aims to design a sustainable two-echelon supply chain not only based on the widely used cost perspective, but also based on the efficient use and preservation of limited resources. For this purpose, a branch and efficiency (B&E) algorithm is developed, which includes an optimization model and an evaluation model. The proposed tri-objective optimization model simultaneously minimizes the total cost of the supply chain, maximizes the sustainability score, and minimizes inequity among customers. The solutions obtained from the optimization model are then evaluated by extended data envelopment analysis (EDEA) models based on common criteria (i.e., cost and service) and traffic congestion criterion. To take into account real-world conditions, parameters related to labor and demand are assumed under uncertainty. Since the presented models consist of more than one objective function, fuzzy goal programming (FGP) method is utilized to tread the multiobjectiveness. The obtained results from tackling a case study problem demonstrate that considering sustainability issues can positively affect both the economic and social aspects of the problem. Furthermore, the developed B&E algorithm is able to reduce costs in each iteration; this is what supply chain managers are interested in. On the other hand, this algorithm can provide more services to applicants compared to one of the competing algorithms.

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Section: Literature Reviewmentioning

confidence: 99%

A branch and efficiency algorithm to design a sustainable two-echelon supply chain network considering traffic congestion and uncertainty

Babaei

Khedmati

Jokar

2022

Environ Sci Pollut Res

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“…DEA is used to compare and evaluate the relative efficiency of similar units with the same responsibilities [18]. It is widely used to solve multi-criteria problems in economic and management, including the evaluation of hospital services performance and supply chain of a shipping company [19,20]. The remainder of the paper is as follows.…”

Section: Introductionmentioning

confidence: 99%

Designing a risk-adjusted CUSUM control chart based on DEA and NSGA-II approaches (a case study in healthcare: Cardiovascular patients)

Rafiei

Asadzadeh

2020

Scientia Iranica

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Researchers have recently devoted a lot of attention to the development of control charts for monitoring healthcare systems. Accordingly, the purpose of this paper is to design a risk-adjusted cumulative sum (CUSUM) control chart to detect decreasing shifts. The proposed chart is used to monitor the survival times of patients who may be subject to an assignable cause such as human mistakes during a surgery. To this end, risk adjustment is performed to consider the impact of each patient's preoperative risks on survival times using survival analysis regression models. However, using the risk-adjusted CUSUM requires that the chart parameters are determined. Hence, a multi-objective economic-statistical model is proposed and a two-stage solution method including non-dominated sorting genetic algorithm (NSGA-II) and Data Envelopment Analysis (DEA) is implemented to solve the model and obtain the optimal design parameters. The performance of the proposed approach is also studied in a real cardiac surgery center. Finally, to confirm the effectiveness of the proposed multi-objective design, two comparisons with the bi-objective and pure economic designs are made. The results show that the performance of the risk-adjusted CUSUM obtained from the proposed model is better than the two other designs considering statistical and economic properties.

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“…The Charnes, Cooper, Rhodes (CCR) model as the most popular DEA model, at first was introduced by Charnes et al in 1978. They idea is to define the efficiency measure by assigning to each unit the most favorable weights as long as the efficiency scores of all DMUs calculated from the same set of weights do not exceed one[35]. Let…”

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confidence: 99%

“…jn . The relative efficiency of DMU k under an assumption of constant returns to scale (CRS) is formulated via the following DEA model[35]:…”

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confidence: 99%

Simulation-Based Optimization using DEA and DOE in Production System

2021

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Production System (PS) is the process of planning, organizing, directing and controlling the tactical and strategic planning of the different components of the company, to transform inputs into finished products which must be effectively managed. Important parts of PS that always face major challenges in manufacturing systems include production strategy, resource allocation, logistics and production planning. Because of the importance of examining the various components of PS and evaluating its performance on key indicators of organization, it is necessary to evaluate the impact of any changes in these elements to the system prior to its creation. In this regard, the present study aimed to increasing the efficiency and determining the useful methods to evaluate and optimize the performance in different part of PS. To this end, an integrated Discrete-Event Simulation (DES), Design of Experiments (DOE), Data Envelopment Analysis (DEA), and Multi-Attribute Decision Making (MADM) models were implemented to analyze and optimize the real PS process. In the case study of the automobile manufacturing industry in Iran, the accurate analysis was applied to the proposed approach and its different aspects were considered as well. The results indicated that the proposed approach is a practical way for evaluating and optimizing the performance of different part of PS, compared to previous models and helps the manufacturing companies to make efficient decisions regarding increasing productivity while decreasing the essential problems.

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Evaluation of Supply Chain of a Shipping Company in Iran by a Fuzzy Relational Network Data Envelopment Analysis Model

Cited by 4 publications

References 35 publications

A branch and efficiency algorithm to design a sustainable two-echelon supply chain network considering traffic congestion and uncertainty

A branch and efficiency algorithm to design a sustainable two-echelon supply chain network considering traffic congestion and uncertainty

Designing a risk-adjusted CUSUM control chart based on DEA and NSGA-II approaches (a case study in healthcare: Cardiovascular patients)

Simulation-Based Optimization using DEA and DOE in Production System

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