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Z-number DEA: A new possibilistic DEA in the context of Z-numbers

ADVANCED ENGINEERING INFORMATICS 2016年第3期30卷 604-617页

作者： Azadeh, Ali Kokabi, Reza Univ Tehran Sch Ind & Syst Engn Coll Engn Tehran 14174 Iran Univ Tehran Ctr Excellence Intelligent Based Expt Mech Coll Engn Tehran 14174 Iran

Data envelopment analysis (DEA) is a methodology that uses multiple inputs and outputs for measuring the efficiencies of a set of decision making units (DMUs). When data are crisp, conventional DEA models are used. However the values of inputs and outputs in many cases are imprecise and vague. In addition, most of these data are expert-based. Thus, taking into account expert's reliability is quite important. In this paper we propose a Z-number version of the CCR (named after Charnes, Cooper, and Rhodes) and BCC (named after Banker, Charnes and Coopers) DEA models. The proposed method can be converted into the fuzzy DEA model when experts are confident about their opinions. Also, it can be converted into the conventional DEA models when the inputs and outputs are crisp numbers. In this study, the Z-number DEA model is transformed into possible linear programming and then by applying an alternative a-cut approach, a crisp linear programming model is obtained. Furthermore, the proposed model is applied to a portfolio selection problem in IS/IT (Information Systems/Information Technology) project to tackle uncertainties, interactions between projects and reliabilities. To the best of our knowledge, this is the first study that presents a unique Z-number DEA model. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Data envelopment analysis (DEA) Fuzzy data envelopment analysis (FDEA) Z-number possibilistic programming Reliability

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Location optimization of wind power generation-transmission systems under uncertainty using hierarchical fuzzy DEA: A case study

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RENEWABLE & SUSTAINABLE ENERGY REVIEWS 2014年 30卷 877-885页

作者： Azadeh, Ali Rahimi-Golkhandan, Armin Moghaddam, Mohsen Univ Tehran Coll Engn Sch Ind Engn Tehran 14174 Iran Univ Tehran Coll Engn Ctr Excellence Intelligent Based Expt Mech Tehran 14174 Iran Michigan Technol Univ Dept Civil & Environm Engn Houghton MI 49931 USA Purdue Univ Sch Ind Engn W Lafayette IN 47907 USA

The use of wind energy as a renewable source of energy is rapidly increasing all over the world as demand for energy is rising. Apart from wind blow, different social and local criteria are important for location optimization of wind power generation-transmission plants. This study presents an integrated fuzzy-DEA approach for decision making on wind plant locations. Besides, an integrated approach incorporating the most relevant indicators of wind plants is introduced. Principal Component Analysis (PCA) and Numerical Taxonomy (NT) are the two multivariate methods used for verification and validation of the results of the DEA model. The proposed model was tested on 25 nominated cities in Iran with 5 regions in each city. In addition, 20 other cities are considered as the consumers of the generated energy. The obtained results indicate the importance of consumers' proximity in wind plant establishment. Moreover, it is shown that fuzzification of uncertain indicators leads to a more realistic approach to this facility location problem. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Wind power generation-transmission plants Location optimization Hierarchical fuzzy data envelopment analysis possibilistic programming

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An accelerated Benders decomposition algorithm for sustainable supply chain network design under uncertainty: A case study of medical needle and syringe supply chain

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2014年第Jul.期67卷 14-38页

作者： Pishvaee, M. S. Razmi, J. Torabi, S. A. Iran Univ Sci & Technol Sch Ind Engn Tehran Iran Univ Tehran Sch Ind Engn Coll Engn Tehran Iran

This paper proposes a multi-objective possibilistic programming model to design a sustainable medical supply chain network under uncertainty considering conflicting economic, environmental and social objectives. Effective social and environmental life cycle assessment-based methods are incorporated in the model to estimate the relevant environmental and social impacts. An accelerated Benders decomposition algorithm utilizing three efficient acceleration mechanisms is devised to cope with computational complexity of solving the proposed model. Computational analysis is also provided by using a medical industrial case study to present the significance of the proposed model as well as the efficiency of the accelerated Benders decomposition algorithm. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Supply chain management Sustainability Benders decomposition possibilistic programming Social responsibility Life cycle assessment

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An integrated fuzzy simulation-fuzzy data envelopment analysis algorithm for job-shop layout optimization: The case of injection process with ambiguous data

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2011年第3期214卷 768-779页

作者： Azadeh, A. Moghaddam, M. Asadzadeh, S. M. Negahban, A. Univ Tehran Univ Coll Engn Dept Ind Engn Tehran 14174 Iran Univ Tehran Univ Coll Engn Ctr Excellence Intelligent Based Mech Tehran 14174 Iran Auburn Univ Dept Ind & Syst Engn Auburn AL 36849 USA

This paper puts forward an integrated fuzzy simulation-fuzzy data envelopment analysis (FSFDEA) algorithm to cope with a special case of single-row facility layout problem (SRFLP). Discrete-event-simulation, a powerful tool for analyzing complex and stochastic systems, is employed for modeling different layout formations. Afterwards, a range-adjusted measure (RAM) is used as a data envelopment analysis (DEA) model for ranking the simulation results and finding the optimal layout design. Due to ambiguousness associated with the processing times, fuzzy sets theory is incorporated into the simulation model. Since the results of simulation are in the form of possibility distributions, the DEA model is treated on a fuzzy basis;therefore, a recent possibilistic programming approach is used to convert the fuzzy DEA model to an equivalent crisp one. The proposed FSFDEA algorithm is capable of modeling and optimizing small-sized SRFLP's in stochastic, uncertain, and non-linear environments. The solution quality is inspected through a real case study in a refrigerator manufacturing company. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Single-row facility layout problem Discrete-event-simulation Data envelopment analysis Fuzzy sets possibilistic programming

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A Multi-Period Location-Allocation-Inventory Problem for Ambulance and Helicopter Ambulance Stations: Robust possibilistic Approach

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IFAC-PapersOnLine 2018年第11期51卷 322-327页

作者： Navazi, F. Tavakkoli-Moghaddam, R. Sazvar, Z. School of Industrial Engineering College of Engineering University of Tehran Tehran Iran

For saving as many as possible human lives, designing an efficient Emergency Medical Services (EMS) network seems necessary, especially by considering world complicated conditions, such as multi-facility locations and multi-transportation modes (e.g., ambulance and helicopter ambulance). The aims of this study are to locate the stations, allocate the accident-prone points to them, determine the required hospital bed capacities provided for patients with critical conditions, and decide about the inventory levels at opened stations including blood banks, medicines, etc. The model is subjected to resource limitation (e.g. budget and a limited number of helicopter ambulances). Since the real-world uncertainty stated by fuzzy numbers, a possibilistic method is used for solving the given problem. To immune solutions in front of fluctuation, it is combined with robust optimization; therefore, a robust possibilistic approach is used. Finally, an augmented ∈-constraint method is used to cope with the bi-objective problem that minimizes the cost and the arrival time. In practice, the model is applied to a real case. © 2018

关键词： Ambulances Budget control Emergency services Fuzzy sets Helicopter services Location Optimization Problem solving Emergency medical services Location allocation Multi facility location possibilistic approach possibilistic programming Resource limitations Robust optimization Transportation mode

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WATER-QUALITY MANAGEMENT WITH IMPRECISE INFORMATION

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 1994年第1期76卷 15-27页

作者： JULIEN, B CTR RECH INFORMAT MONTREAL 1801 MCGILL COLL AV OFF 800 MONTREAL H3A 2N4 PQ CANADA

The application of fuzzy set and possibility theories for the representation of imprecise information in water quality management problems is investigated. Imprecision is associated with fuzziness which is non-statistical in nature and refers to the absence of sharp boundaries in the information. Imprecise parameters in water quality decision-making can be represented by possibility distributions defining maximum achievable probabilities. The corresponding possibilistic programming problem is viewed as an alternative to the stochastic one where the parameters are modeled as fuzzy variables instead of random variables. The possibilistic problem can be solved through a succession of classical linear programs. The resulting possibility distributions of the objective value provide a possibilistic assessment of the risk based on possibility levels.

关键词： WATER MANAGEMENT FUZZY SETS POSSIBILITY THEORY LINEAR programming possibilistic programming

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A new mathematical model for designing and improving the performance of a home health care logistics network

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ANNALS OF OPERATIONS RESEARCH 2024年第2-3期340卷 1189-1220页

作者： Akhondi-Bajegani, Esmaeil Jolai, F. Torabi, S. Ali Univ Tehran Coll Engn Sch Ind Engn Tehran Iran

To provide better care for the elderly, health trustees establish home health care centers in cities. These centers offer services at homes, and a logistics network is essential for providing these services. An integrated framework is developed to design such a network by which various logistical decisions are made under inherent epistemic uncertainty of the travel and service times. A new mixed integer linear programming model is developed, and its equivalent deterministic formulation is obtained using a well-applied possibilistic programming approach. An improved genetic algorithm is also devised to solve large-sized instances and various sensitivity analyses are performed on key factors. Finally, a case study is presented to validate the developed model and its solution method. The numerical results demonstrate 20% reduction in the total time of employing care givers at almost 3.5% cost savings.

关键词： Home health care Network design possibilistic programming Improved genetic algorithm

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A dual-channel multi-objective green supply chain network design considering pricing and transportation mode choice under fuzzy uncertainty

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ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY 2024年第5期27卷 10341-10372页

作者： Rezakhanlou, Maryam Al-e-Hashem, Seyed Mohammad Javad Mirzapour Amirkabir Univ Technol Tehran Polytech Dept Ind Engn & Management Syst Tehran Iran

Today, given the rising trend of e-commerce businesses, supply chain management in such chains has attracted the attention of academic societies. This research presents a multi-objective programming model to configure a dual-channel (conventional and e-commerce channels) supply chain network structure under triple uncertain sources, which jointly optimizes the allocating, pricing, and transporting decisions. Furthermore, considering the growing concerns on environmental sustainability, the environmental dimensions of the dual-channel supply chain are contributed. The proposed model minimizes the Carbon dioxide (CO2) emissions associated with transportation and the production process as an objective function to meet environmental standards. Multiple modes of transportation with different costs and CO2 emissions are considered in each distribution channel. The multi-objective fuzzy optimization model is solved by developing a fuzzy solution approach following the linearization of the proposed model. Through the use of numerical examples, the validity of the developed model and the usefulness of the solution method are demonstrated. The sensitivity analysis has also been performed to see the impact of changing some essential parameters on objective functions. The results show that the profit and environmental performance of the two-channel supply chain improve when more goods are shipped through the traditional channel than through the direct channel.

关键词： Network design Green supply chain Dual-channel supply chain Pricing possibilistic programming Fuzzy multi-objective optimization

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An enhanced reverse auction framework for relief procurement management

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INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION 2017年 24卷 66-80页

作者： Shokr, Iman Torabi, S. Ali Univ Tehran Sch Ind Engn Coll Engn Tehran Iran

An enhanced reverse auction framework is developed for procuring excess required relief items for humanitarian organizations at post-disaster. Given the input data tainted with epistemic uncertainty, two novel possibilistic models are developed to support the bidders and the auctioneer who is a coordinating platform (CP), regarding the bid construction and bid evaluation, respectively. First, using the bid construction model, competing suppliers determine their suggestions regarding the unit prices, quantities, and delivery times of relief items as well as the most appropriate transportation modes. Afterwards, the CP runs the bid evaluation model to assess the submitted bids by which the best portfolio of suppliers and their allocated orders are determined. An illustrative numerical example inspired by a real practice is provided to demonstrate the applicability of the proposed decision models. Several sensitivity analyses are also conducted on key parameters from which useful managerial insights are drawn.

关键词： Humanitarian logistics Post-disaster procurement Reverse auction possibilistic programming

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Integrated resilient and sustainable gasoline supply chain model with operational and disruption risks: a case study of Iran

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ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY 2024年 1-73页

作者： Khalili, Seyed Mohammad Pooya, Alireza Kazemi, Mostafa Saghih, Amir Mohammad Fakoor Ferdowsi Univ Mashhad Fac Econ & Adm Sci Dept Management Mashhad Iran

Recent extreme economic, social, and environmental changes have made the design of gasoline supply chain (GSC) networks a major challenge, while sustainability and resilience are emerging as the concerns of communities. This paper presents a novel two-stage scenario-based mixed stochastic-possibilistic programming model for designing a three-echelon GSC by considering sustainability and resilience criteria simultaneously. The configuration of the network and pre-disruption risk mitigation options are determined in the first stage of the model, whereas distribution plans, reconfiguration of the chain, and restoration of the lost capacities are delineated in the second stage. Resilience dimensions, including design quality, and proactive and reactive capabilities, are considered in the design of the chain, and sustainability criteria are addressed via the cost of network establishment, environmental effects of CO2 emissions, and social effects of the network development on improving job opportunities or economic conditions of local areas. The solution procedure includes scenario planning, handling imprecise parameters, determining scenario-based variables, and finding the Pareto Front. Notably, for the sake of handling high-impact, low-probability disruption scenarios, i.e., disruption scenarios, this research proposes a novel version of the conditional value at risk measure called augmented-CVaR. The validation of the proposed model is examined through a real-world case study in Iran.

关键词： Supply chain Resilience Sustainability Gasoline possibilistic programming

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