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The Flexible possibilistic-Robust Mathematical programming Approach for the Resilient Supply Chain Network: An Operational Plan

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JOURNAL OF ADVANCED MANUFACTURING SYSTEMS 2021年第3期20卷 473-498页

作者： Hamidieh, Alireza Arshadikhamseh, Alireza Payamnoor Univ Engn Dept Tehran Iran Kharazmi Univ Engn Dept Tehran Iran

Nowadays, the management of soil resources for global food security is one of the strategic purposes of the countries. In this regard, creating soil nutrition's supply chain network for the fertility of agricultural fields is one of the most critical priorities of the government. In the above strategic network, we are faced with uncertain parameters that show a complex behavior under time, geography, and market changes. This parametric uncertainty is aggravated by the occurrence of disruptions such as sanctions and natural disasters, with devastating effects on strategic, tactical, and operational decisions. In this paper, by adopting a set of reactive and preventive strategies, the resilient supply chain network of dependent petrochemical industries is presented, consistent with the structure of its production cycle in Iran. To cope with the uncertainty, a robust programming approach was extended into flexible-possibilistic programming. The final model controls the uncertainty and risk-aversion of output decisions and effectively confronts the adverse effects of disruptions. Finally, using a real industrial study, the effectiveness and applicability of the final model are explained. Furthermore, by providing efficient solutions, mean cost and minimum standard deviations were achieved.

关键词： Supply chain robust resilient possibilistic programming uncertainty

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A supply chain design for creating microalgae-based biodiesel considering resources nexus and uncertainty

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COMPUTERS & CHEMICAL ENGINEERING 2025年 197卷

作者： Zarrinpoor, Naeme Govindan, Kannan Shiraz Univ Technol Dept Ind Engn Shiraz Iran Shanghai Maritime Univ China Inst FTZ Supply Chain Shanghai Peoples R China Univ Adelaide Ctr Sustainable Operat & Resilient Supply Chains Adelaide Business Sch Adelaide SA 5005 Australia Univ Adelaide Inst Sustainabil Energy & Resources Adelaide SA 5005 Australia

This research aims to offer a biodiesel supply chain design by utilizing microalgae as the feedstock. The model examines both economic optimization and the intricately interconnected nexus of natural resources so that overall costs, water consumption, released emissions, and food loss are all minimized, and the amount of clean energy production is maximized. In order to prevent diminishing fresh water supplies, this study employs sewage and saline water as additional sources of water. Furthermore, the suggested model employs sewage water as a source of nutrients to reduce fertilizer rivalry between biomass and agricultural output. The model accounts for the uncertainty of important characteristics including costs, resources availability, and demand. A handling method for uncertainty based on robust optimization, possibilistic programming, and flexible programming is created. An Iranian case study is utilized to verify the model and uncertainty handling method.

关键词： Biodiesel supply chain Microalgae Resources nexus Robust optimization Flexible programming possibilistic programming

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Multi-Objective Blood Supply Chain Network Design Under Uncertainty: Integrating Environmental and Social Considerations

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PROCESS INTEGRATION AND OPTIMIZATION FOR SUSTAINABILITY 2025年第2期9卷 625-650页

作者： Sheibani, Mehrzad Ostovari, Alireza Benyoucef, Lyes Shiraz Univ Technol Dept Ind Engn Shiraz Iran Aix Marseille Univ CNRS LIS Marseille France

Blood and its products are considered one of the most critical medical needs. Factors such as irregular supply and demand, lack of technology to produce blood and dependence on donation, different types of blood, perishability, and mortality of people in the event of a blood shortage have increased the importance of blood in people's lives. To address these challenges, this paper presents a mix integer linear programming model for a blood supply chain network based on sustainable development goals under uncertainty that includes collecting, processing, holding, and delivering various blood products. More specifically, a multi-objective, multi-period, and multi-product mathematical programming model is proposed to minimize total costs, minimize environmental damage, and maximize social effects resulting from the implementation of the network. The proposed model can help managers in hospitals and the blood transfusion organizations in making important strategic, tactical, and operational decisions such as where to locate blood facilities, the flow of different products between facilities, assigning donor groups to blood facilities, and inventory control decisions. First, a robust possibilistic programming approach is utilized to deal with the uncertainty of the mathematical model. Second, an interactive fuzzy programming method is used to solve the proposed model. The efficacy of the mathematical model is evaluated using real data from the Shiraz metropolitan area in Iran. Finally, the mathematical model's behavior was analyzed using sensitivity analyses on the main factors. The experimental results show the efficiency of the model in the satisfaction of demand and the reduction of waste.

关键词： Blood supply chain Mix integer linear programming possibilistic programming Sustainable development Robust optimization

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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 2025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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Weighted Linear Fractional programming for possibilistic Multi-objective Problem 4

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4th INNS Symposia on Computational Intelligence in Information Systems (INNS-CIIS)

作者： Arbaiy, Nureize Univ Tun Hussein Onn Malaysia Batu Pahat 86400 Malaysia

ISBN: (纸本)9783319131535;9783319131528

The assessment of the weights of objective function plays an important role in a multi-objective process. This paper discusses a weighting method for linear fractional programming to solve possibilistic programming of the multi-objective decision-making problem. The minimal and maximal values of the objective function are utilized in the determination the weight value. This analysis concludes that it is worthwhile to pursue proposed solution approach to the multi-objective evaluation scheme, which addresses some limitation to determine the weight values.

关键词： Weighting method Multi-objective problem possibilistic programming Linear fractional

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A novel model for multi-criteria assessment based on BWM and possibilistic chance-constrained programming

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COMPUTERS & INDUSTRIAL ENGINEERING 2021年 156卷 107287-107287页

作者： Amiri, Maghsoud Hashemi-Tabatabaei, Mohammad Ghahremanloo, Mohammad Keshavarz-Ghorabaee, Mehdi Zavadskas, Edmundas Kazimieras Antucheviciene, Jurgita Allameh Tabatabai Univ Fac Management & Accounting Dept Ind Management Tehran *** Iran Shahrood Univ Technol Fac Ind Engn & Management Dept Management Shahrood *** Iran Gonbad Kavous Univ Fac Humanities Dept Management Azadshahr Branch Gonbad Kavous *** Iran Vilnius Gediminas Tech Univ Civil Engn Fac Inst Sustainable Construct Sauletekio 11 LT-10223 Vilnius Lithuania Vilnius Gediminas Tech Univ Dept Construct Management & Real Estate Sauletekio 11 LT-10223 Vilnius Lithuania

The best-worst method (BWM) is one of the most important methods for determining the weights of criteria or options in multi-criteria decision-making (MCDM) and has attracted the attention of many researchers due to its advantages such as fewer numbers of comparisons and higher consistency rate. Given that real-world decision making is often associated with uncertainty, in this study several fuzzy linear programming models have been developed using trapezoidal fuzzy numbers for BWM that can calculate the optimal weights of criteria. The proposed models are based on three measures of possibility, necessity, and credibility, which are parts of possibilistic chance-constrained programming (PCCP). Development of BWM based on possibilistic distribution allows the decision-maker (DM) to take into account uncertainties in the calculation of weights as well as include his optimistic, pessimistic, and intermediate attitudes in determining the weight of decision criteria. The possibility approach reflects the DM's optimistic view of the issue. The necessity approach is used in situations where the DM prefers a pessimistic view, and the credibility approach indicates that DM has an intermediate view between optimistic and pessimistic views, or in other words, considers an intermediate approach between possibility and necessity approaches. Finally, the feasibility and effectiveness of the proposed approaches were tested using two numerical examples and the sensitivity of the results was analyzed for different values of uncertainty (alpha parameter). Also, by analyzing the coefficient of variation, it was found that the results of the proposed models had very little dispersion for different values of uncertainty, and this confirmed the validity of the results. Examining the results of the proposed models revealed that the possibility approach provides more robust results than other approaches when the levels of confidence of the decision-makers are changed.

关键词： Multi-criteria decision-making possibilistic programming Best-worst method Pairwise comparison Fuzzy linear programming

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Fuzzy chance-constrained data envelopment analysis: a structured literature review, current trends, and future directions

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FUZZY OPTIMIZATION AND DECISION MAKING 2022年第2期21卷 197-261页

作者： Peykani, Pejman Hosseinzadeh Lotfi, Farhad Sadjadi, Seyed Jafar Ebrahimnejad, Ali Mohammadi, Emran Iran Univ Sci & Technol Sch Ind Engn Tehran Iran Islamic Azad Univ Sci & Res Branch Dept Math Tehran Iran Islamic Azad Univ Qaemshahr Branch Dept Math Qaemshahr Iran

Fuzzy data envelopment analysis (FDEA) is one of the most applicable approaches for performance assessment of peer decision making units under ambiguity which is evolving rapidly and gaining popularity under uncertain data envelopment analysis field. The goal of this paper is to review some FDEA models based on applied possibility, necessity, credibility, general fuzzy measures and chance-constrained programming to deal with data ambiguity. The study presents a comprehensive and structured literature review of fuzzy chance-constrained data envelopment analysis (FCCDEA) studies including 87 studies from 2000 to 2020. The main contributions of this research include the following details: (1) Review of fuzzy chance-constrained programming, (2) Survey of FCCDEA models based on different fuzzy measures, (3) Analysis of FCCDEA applications and features, (4) Classification of FCCDEA studies from modeling and uncertainty type viewpoints, (5) Bibliometric analysis of FCCDEA literature, and (6) Extraction of main research gaps and guidelines for future research directions.

关键词： Data envelopment analysis (DEA) Fuzzy optimization Fuzzy DEA (FDEA) Chance-constrained programming (CCP) possibilistic programming Fuzzy measure

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Organ transportation and allocation problem under medical uncertainty: A real case study of liver transplantation

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2020年 134卷 101841-101841页

作者： Kargar, Bahareh Pishvaee, Mir Saman Jahani, Hamed Sheu, Jiuh-Biing Iran Univ Sci & Technol Sch Ind Engn Tehran Iran RMIT Univ Sch Business IT & Logist Melbourne Vic 3000 Australia Natl Taiwan Univ Dept Business Adm Taipei Taiwan

Organ allocation is the most important decision amongst organ transplantation decisions thanks to the high demand of organs. This research develops a possibilistic programming model for a liver transportation and allocation problem considering medical uncertainty and tradeoff between quality metrics, namely efficiency and equity. The model maximizes the survival rate of patients and minimizes the transportation cost and time. A novel hybrid interactive fuzzy optimization model is developed based on preemptive goal programming approach. Several numerical examples are taken from a real case study. The results demonstrate that the suggested algorithm outperforms the existing allocation policy, considering both metrics.

关键词： Organ transplantation Organ transportation network Fuzzy sets possibilistic programming Preemptive goal programming

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Business continuity-inspired resilient supply chain network design

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2021年第5期59卷 1331-1367页

作者： Namdar, Jafar Torabi, S. Ali Sahebjamnia, Navid Nilkanth Pradhan, Ninad Univ Iowa Tippie Coll Business Dept Business Analyt Iowa City IA USA Univ Tehran Coll Engn Sch Ind Engn Tehran Iran Univ Sci & Technol Mazandaran Dept Ind Engn Behshahr Iran Univ Tennessee Knoxville TN USA

Supply chains are prone to several operational and disruption risks. In order to design a resilient supply chain network capable of responding to such potential risks suitably, this paper proposes a novel framework for the business continuity-inspired resilient supply chain network design (BCRSCND) problem, which includes three steps. First, four resilience dimensions including Anticipation, Preparation, Robustness, and Recovery are considered to quantify the resilience score of each facility using a multi-criteria decision-making technique and considering a comprehensive set of resilience strategies. In the second step, the critical processes and their business continuity metrics (which are vital for supply chain continuity), are identified. The outputs of the first two steps provide the inputs of a novel two-stage mixed possibilistic-stochastic programing (TSMPSP) model. The model aims to design a multi-echelon, multi-product resilient supply chain network under both operational and disruption risks. The proposed TSMPSP model allows decision makers to incorporate their risk attitudes into the design process. After converting the original TSMPSP model into the crisp counterpart, several sensitivity analyses are conducted on different features of hypothetical disruptions (i.e. their severity, likelihood and location) and DM's risk attitudes from which useful managerial insights are provided.

关键词： Resilience management supply chain design business continuity management two-stage stochastic programming possibilistic programming

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Large-scale disaster waste management under uncertain environment

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JOURNAL OF CLEANER PRODUCTION 2019年 212卷 200-222页

作者： Habib, Muhammad Salman Sarkar, Biswajit Tayyab, Muhammad Saleem, Muhammad Wajid Hussain, Amjad Ullah, Mehran Omair, Muhammad Iqbal, Muhammad Waqas Univ Engn & Technol Lahore Dept Ind & Mfg Engn Lahore Pakistan Hanyang Univ Dept Ind & Management Engn Ansan 15588 Gyeonggi Do South Korea Univ Engn & Technol Lahore Dept Mech Engn Lahore Pakistan

The phenomena of global warming have increased the frequency of natural disasters. These disasters generate thousands of tons of waste and cause loss of human lives, environmental damages, and economic losses every year. Currently, disaster response policies are reactive in nature to bring the community back to normal routine. However, increased resilience against future disasters can be achieved by working on long-term planning and setting goals for ecological, economic, and social sustainability in disaster response policies. Keeping in view the importance of the considered issue, this study proposes a large-scale disaster waste management supply chain model, considering economic aspect via total waste processing, environmental aspect by greenhouse gas emissions from disaster waste processing, and social aspect by job opportunities generated during waste processing. To demonstrate the applicability of the proposed supply chain model, numerical experiments are performed on a large-scale case problem. Results show that there is a strong trade-off among the dimensions of sustainability. If decision makers want to achieve higher satisfaction levels against environmental and social objectives, the operational cost of waste management will increase accordingly. Numerical studies obtain the results in accordance with the values of the confidence level of decision makers and coefficient of compensation decided by the managers which also provides the flexibility for the decision makers of developing countries to obtain preferred compromised solution in accordance with their own preferences for the dimensions of sustainability during disaster waste management operation. (C) 2018 Published by Elsevier Ltd.

关键词： Sustainable disaster waste management Greenhouse gas emissions Disaster waste recycling Social sustainability possibilistic programming

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