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A New Combination of Robust-possibilistic Mathematical programming for Resilient Supply Chain Network under Disruptions and Uncertainty: A Real Supply Chain

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INTERNATIONAL JOURNAL OF ENGINEERING 2018年第4期31卷 612-621页

作者： Hamidieh, A. Khamseh, A. Arshadi Naderi, B. Kharazmi Univ Fac Engn Dept Ind Engn Tehran Iran

Nowadays, the design of a strategic supply chain network under disruption is one of the most important priorities of the governments. One of the strategic purposes of managers is to supply the sustainable agricultural products and food in stable conditions which require the production of soil nutrients. In this regard, some disruptions such as sanctions and natural disasters have a destructive effect on the supply of raw materials and the uncertainty of input parameters plays an undesirable impact on the decision-making levels including strategic, tactical, and operational levels. The present study introduced a new model of resilient supply chain network which was compatible with the realities of the structure of the supply chain for fertilizer in Iran. Notably, the effectiveness of the designed system was promoted by the dominant strategies of reliability. Further, a new robust possibilistic approach was proposed which guaranteed the optimality and feasibility robustness through the efficient solution to deal with the parametric uncertainty. Finally, the results showed that the proposed new robust possibilistic combination promoted the optimality robustness and its effectiveness using an optimal average cost and minimum standard deviation.

关键词： Supply Chain possibilistic programming Disruption Robustness Uncertainty

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DESIGNING A SUSTAINABLE CLOSED-LOOP SUPPLY CHAIN USING ROBUST possibilistic-STOCHAS TIC programming IN PENTAGONAL FUZZY NUMBERS

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TRANSPORT 2024年第4期39卷 323-349页

作者： Dehshiri, Seyyed Jalaladdin Hosseini Amiri, Maghsoud Hajiaghaei-keshteli, Mostafa Keshavarz-ghorabaee, Mehdi Zavadskas, Edmundas Kazimieras Antucheviciene, Jurgita Allameh Tabatabai Univ Dept Ind Management Tehran Iran Monterrey Inst Technol & Higher Educ Dept Ind Engn Puebla Mexico Gonbad Kavous Univ Dept Management Gonbad Kavous Iran Vilnius Gediminas Tech Univ Inst Sustainable Construct Vilnius Lithuania Vilnius Gediminas Tech Univ Dept Construct Management & Real Estate Vilnius Lithuania

The lack of information and hybrid uncertainties in Supply Chain (SC) parameters affect managerial decisions. It is inevitable to consider random uncertainty based on fuzzy scenarios and cognitive uncertainty to prehensiveness and accuracy than triangular and trapezoidal fuzzy numbers due to taking into account higher uncertainty, less lack of information, and taking into account maximum subjectivity Decision-Makers (DMs). There is a gap in the literature regarding the use of PFNs in SCLSC problems. This research presents a new model using PFNs to solve deficiencies in stochastic-possibilistic programming. Developing a Robust Stochastic-possibilistic (RSP) based on PFNs under fuzzy scenarios, presenting measures of necessity, possibility, and credibility for making decisions founded on different levels of DMs' risk, and proposing global solutions through providing linear programming models are the main innovations and contributions of the present research. An actual case study evaluates the presented approach to reduce the cost and carbon pollution in the stone paper SC. In the suggested method, trade-offs could be formed between the mean of objective functions and risk by modifying the robustness coefficients. According to the proposed approach, an optimal value of confidence is specified. Additionally, robustness deviations are controlled in the model, which results in more accurate and reliable results. Numerical simulations confirmed the efficacy of the robust approach proposed.

关键词： closed-loop supply chain possibilistic programming fuzzy scenarios robust approach sustainable design stochastic programming

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An interactive possibilistic programming approach for a multi-objective closed-loop supply chain network under uncertainty

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INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE 2014年第3期45卷 283-299页

作者： Fallah-Tafti, Alireza Sahraeian, Rashed Tavakkoli-Moghaddam, Reza Moeinipour, Masoud Shahed Univ Fac Engn Dept Ind Engn Tehran Iran Univ Tehran Coll Engn Dept Ind Engn Tehran Iran Khajeh Nasir Toosi Univ Technol Fac Mech & Ind Engn Dept Ind Engn Tehran Iran

In this article, we first propose a closed-loop supply chain network design that integrates network design decisions in both forward and reverse supply chain networks into a unified structure as well as incorporates the tactical decisions with strategic ones (e.g., facility location and supplier selection) at each period. To do so, various conflicting objectives and constraints are simultaneously taken into account in the presence of some uncertain parameters, such as cost coefficients and customer demands. Then, we propose a novel interactive possibilistic approach based on the well-known STEP method to solve the multi-objective mixed-integer linear programming model. To validate the presented model and solution method, a numerical test is accomplished through the application of the proposed possibilistic-STEM algorithm. The computational results demonstrate suitability of the presented model and solution method.

关键词： closed-loop supply chain network design possibilistic programming STEP method multiple-criteria decision making supplier selection

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A hybrid fuzzy-stochastic multi-criteria ABC inventory classification using possibilistic chance-constrained programming

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SOFT COMPUTING 2021年第2期25卷 1065-1083页

作者： Razavi Hajiagha, Seyed Hossein Daneshvar, Maryam Antucheviciene, Jurgita Khatam Univ Fac Management & Finance Dept Management Tehran Iran Vilnius Gediminas Tech Univ Dept Construct Management & Real Estate Sauletekio Ave 11 LT-10223 Vilnius Lithuania

Inventory classification is a fundamental issue in the development of inventory policy that assigns each inventory item to several classes with different levels of importance. This classification is the main determinant of a suitable inventory control policy of inventory classes. Therefore, a great deal of research is done on solving this problem. Usually, the problem of inventory classification is considered in a multi-criteria and uncertain environment. The proposed method in this paper inspired by the notion of heterogeneous decision-making problems in which decision-makers deal with different types of data. To this aim, a mathematical modeling-based approach is proposed considering different types of uncertainty in classification information. Demand information is considered to be stochastic due to its time-varying nature and cost information is considered to be fuzzy due to its cognitive ambiguity. A hybrid algorithm based on chance-constrained and possibilistic programming is proposed to solve the problems. Considering the stochastic nature of demand information, solving the proposed model using the hybrid algorithm, the classification of items to three classes of extremely important, class A, moderately important, class B, and relatively unimportant, class C, items are determined along with a minimum inventory level required to deal with the stochasticity of demands information. The proposed approach is applied to a case study of classifying 51 inventory items. The obtained results assigned 22%, 39%, and 39% of the items to A, B, and C classes, respectively.

关键词： Multi-criteria inventory classification Chance-constrained programming possibilistic programming

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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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Notes on "possibilistic programming approach for fuzzy multidimensional analysis of preference in group decision making"

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COMPUTERS & INDUSTRIAL ENGINEERING 2014年第1期73卷 1-4页

作者： Li, Deng-Feng Fuzhou Univ Sch Econ & Management Fuzhou 350108 Fujian Peoples R China

The aim of this note is to point out and correct some errors in the definitions, notations operations and possibilistic programming model introduced by Sadi-Nezhad and Akhtari (2008) and hereby develop two correct possibilistic programming models for fuzzy multidimensional analysis of preference in the fuzzy multiattribute group decision making problems with both the fuzzy weight vector and the fuzzy positive ideal solution (PIS) unknown a priori. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： possibilistic programming Linear programming techniques for multidimensional analysis of preference (LINMAP) Multiobjective linear programming Fuzzy multiattribute group decision making Fuzzy number

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Imprecise Project Network Scheduling Using possibilistic programming Approach

Imprecise Project Network Scheduling Using Possibilistic Pro...

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2014 International Conference on Fuzzy Theory and Its Applications

作者： Liang, Tien-Fu Lin, Hsueh-Mao Cheng, Hung-Wen Chen, Yi-Fen Hsiuping Univ Sci & Technol Dept Ind Engn & Management Taichung Taiwan

ISBN: (纸本)9781479945887

This work develops a possibilistic programming approach to solve imprecise project network scheduling (PNS) problems with multiple goals. The imprecise multi-objective PNS model designed here attempts to minimize total project costs and total completion time with reference to direct costs, indirect costs, contractual penalty costs, duration of activities and the constraint of available cost budget. An industrial case is used to demonstrate the feasibility of applying the proposed approach to real-life PNS problems. Several significant managerial implications for practical application of the proposed approach are also presented. The important contribution of this work lies in presenting a possibilistic mathematical programming methodology for solving the practical multi-objective PNS problems.

关键词： Project network scheduling Fuzzy sets possibilistic programming Multi-objective linear programming

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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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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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Designing the agile green sustainable multi-channel closed-loop supply chain with dependent demand to price and greenness under epistemic uncertainty

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EUROPEAN JOURNAL OF INDUSTRIAL ENGINEERING 2024年第4期18卷 557-605页

作者： Tajani, Elham Kouchaki Kanafi, Armin Ghane Daneshmand-Mehr, Maryam Hosseinzadeh, Ali-Asghar Islamic Azad Univ Dept Ind Engn Lahijan Branch Lahijan Iran Islamic Azad Univ Dept Math Lahijan Branch Lahijan Iran

The increasing pressure and intensity of world competition in business environments, which is ever-changing, has doubled the necessity of proper reactions by industrial manufacturing organisations and companies. Therefore, this paper proposes a novel design of a closed-loop supply chain with multiple forms of product distribution and collection that aim to maximise profit and social responsibility while minimising delays in delivery and environmental pollution. The proposed model uses two indices, local employment and the number of jobs created, to show the performance of the function of social responsibility. Further, by mentioning pricing and greenness levels for the products in the paper, we formulate customer demands dependent on the price and greenness of the products. Also, RFID technology is considered for every vehicle to reduce time lags during transportation. Besides, the modelling is performed according to a possibilistic mean-absolute deviation approach due to the uncertain nature of some parameters. Eventually, the augmented epsilon-constraint method is utilised to solve and its validation. The results revealed that the proposed model could provide efficient decisions that can be a suitable tool for managers and experts, and it can have extensive application, particularly from a strategic perspective.

关键词： multi-channel pricing RFID possibilistic programming

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