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fuzzy parametric programming model for multi-objective integrated solid waste management under uncertainty

EXPERT SYSTEMS WITH APPLICATIONS 2012年第5期39卷 4657-4678页

作者： Srivastava, Amitabh Kumar Nema, Arvind K. Bundelkhand Inst Engn & Technol Jhansi 284128 Uttar Pradesh India Indian Inst Technol Delhi Dept Civil Engn New Delhi 110016 India

Solid waste management is increasingly becoming a challenging task for the municipal authorities due to increasing waste quantities, changing waste composition, decreasing land availability for waste disposal sites and increasing awareness about the environmental risk associated with the waste management facilities. The present study focuses on the optimum selection of the treatment and disposal facilities, their capacity planning and waste allocation under uncertainty associated with the long-term planning for solid waste management. The fuzzy parametric programming model is based on a multi-objective, multi-period system for integrated planning for solid waste management. The model dynamically locates the facilities and allocates the waste considering fuzzy waste quantity and capacity of waste management facility. The model addresses uncertainty in waste quantity as well as uncertainties in the operating capacities of waste management facilities simultaneously. It was observed that uncertainty in waste quantity is likely to affect the planning for waste treatment/disposal facilities more as compared with the uncertainty in the capacities of the waste management facilities. The relationship between increase in waste quantity and increase in the total cost/risk involved in waste management is found to be non-linear. Therefore, it is possible that a marginal change in waste quantity could increase the total cost/risk substantially. The information obtained from the analysis of modeling results can be effectively used for understanding the effect of changing the priorities and objectives of planning decisions on facility selections and waste diversions. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Solid waste management Integrated solid waste management system Long term planning Multi-objective and multi-period planning fuzzy parametric programming

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fuzzy reliability-redundancy allocation problem of the overspeed protection system

ENGINEERING REPORTS

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ENGINEERING REPORTS 2020年第8期2卷

作者： Taghiyeh, Sajjad Mahmoudi, Morteza Fadaie, Saber Tohidi, Hossein North Carolina State Univ Edwards P Fitts Dept Ind & Syst Engn Raleigh NC 27695 USA Iran Univ Sci Technol Sch Ind Engn Tehran Iran Univ Tafresh Dept Ind Engn Tafresh Iran

System reliability is defined as the probability of satisfactory performance of a system under stated conditions for a specified period of time. According to this definition, four parameters, including probability, satisfactory performance, specific conditions, and time should be exactly characterized to evaluate the system reliability accurately. However, due to the uncertainty involved in real situations, it is hardly possible to assess the aforementioned parameters precisely. In this article, two general and distinct approaches, including Zadeh's extension principle and modification of fuzzy parametric programming (FPP), are proposed to take into account such uncertainty in a famous reliability problem called the overspeed protection system. According to Zadeh's extension principle, a pair of nonlinear programming problems is formulated to compute..-level cuts of fuzzy system reliability. Themembership function of fuzzy system reliability can then be constructed analytically by numerating different values of... This fuzzy system reliability presents flexibility for further system analysis. In the second approach, from a different point of view, a variant of FPP is improved that provides a crisp value as a system reliability measure. The rewarding point of the latter procedure is to handle the problem in a computationally easier way.

关键词： extension principle fuzzy parametric programming fuzzy sets nonlinear programming redundancy allocation problem system reliability

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fuzzy parametric programming Model for Integrated Solid Waste Management under Uncertainty

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JOURNAL OF ENVIRONMENTAL ENGINEERING 2011年第1期137卷 69-83页

作者： Srivastava, Amitabh Kumar Nema, Arvind K. Bundelkhand Inst Engn & Technol Jhansi 284128 Uttar Pradesh India Indian Inst Technol Delhi Dept Civil Engn New Delhi 110016 India

Solid waste management (SWM) is increasingly becoming a challenging task for the municipal authorities due to increasing waste quantities, changing waste composition, decreasing land availability for waste disposal sites, and increasing awareness about the associated environmental risk. This paper presents a fuzzy parametric programming model for the selection of the treatment and disposal facilities and optimum capacity planning and waste allocation under uncertainty associated with the long-term planning for SWM. The model dynamically locates the facilities and allocates the waste considering fuzzy waste quantities and capacities of waste-management facility in a multiperiod planning for integrated SWM. The model addresses uncertainty in waste quantity as well as uncertainties in the operating capacities of waste-management facilities. An example problem has been presented to demonstrate the usefulness of the proposed model in making the planning decisions related to SWM and achieving an efficient plan. The model is solved at different levels of membership function for the alternative solutions with respect to objective. The example problem reveals that the uncertainty in the waste quantity is likely to affect the planning for waste treatment/disposal facilities more as compared with the uncertainty in the capacities of the waste-management facilities. The relationship between increase in waste quantity and increase in the total cost involved in waste management is found to be nonlinear. The modeling results are useful for generating a range of decision alternatives under various economic conditions. They are valuable for analyzing the existing waste-management practices, the long-term capacity planning for the city's waste-management system, and the identification of desired policies regarding waste generation and management.

关键词： Solid waste management Integrated solid waste-management system Long-term planning fuzzy parametric programming

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An extended fuzzy parametric programming-based approach for designing cellular manufacturing systems under uncertainty and dynamic conditions

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INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING 2009年第6期22卷 538-548页

作者： Safaei, N. Tavakkoli-Moghaddam, R. Univ Toronto Dept Mech & Ind Engn Toronto ON M5S 3G8 Canada Univ Tehran Coll Engn Dept Ind Engn Tehran Iran

This paper proposes an extended fuzzy parametric programming (FPP) approach to solve a dynamic cell formation problem considering the uncertain part demand and machine capacity. The classical FPP approach gives the decision maker a number of alternative decisions for different grades of precision. Linear membership functions such as trapezoid, triangular and other piecewise forms have widely been used to express the uncertain parameters in the different engineering fields. Especially, to our best of knowledge, all researches related to the use of the fuzzy programming-based approaches for cellular manufacturing systems (CMSs) have been applied to the piecewise membership functions. In the case of lack of sufficient knowledge, there is a section in the piecewise forms called 'core', consisting of the fully included members (i.e. members with membership degree equal to one). This section, which represents the expert's ignorance, is not considered in the fuzzy programming-based approaches presented in the literature. In a highly cost-intensive production system, such as cellular manufacturing systems, the decision maker wants to know how big the changes of the cell configuration from one period to another are. These changes are caused by the fluctuations in some parameters of the system, such as part demand and machine capacity. However, when these parameters are uncertain as well as dynamic, the risk of decision making will increase significantly. On the other hand, in practice, a domain of uncertainty of data corresponds to a unique decision and hence the whole uncertainty in the system can be covered by only a few numbers of the alternative decisions, called 'applicable decisions'. This reduction in the decision space gives a better idea to the decision maker to make the final decision. The extended FPP proposed in this paper uses a simple strategy to extract all possible applicable solutions resulting from the core of the membership functions of the uncertain param

关键词： cellular manufacturing system dynamic and uncertain environment mixed-integer programming fuzzy parametric programming

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The use of multi-criteria data envelopment analysis (MCDEA) for location-allocation problems in a fuzzy environment

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EXPERT SYSTEMS WITH APPLICATIONS 2011年第5期38卷 5687-5695页

作者： Moheb-Alizadeh, H. Rasouli, S. M. Tavakkoli-Moghaddam, R. Univ Tehran Coll Engn Dept Ind Engn Tehran Iran Univ Tehran Coll Engn Ctr Excellence Intelligence Based Expt Mech Tehran Iran Tarbiat Moallem Univ Fac Engn Dept Ind Engn Tehran Iran

This paper incorporates the concept of efficiency defined by data envelopment analysis (DEA) into location-allocation models in a fuzzy environment. It is shown how this incorporation can influence the pattern of facility location and the assignment of demands. Due to two major shortcomings, called low discrimination power and unrealistic weight distribution associated with classic form of DEA, a multi-criteria DEA is applied. Since the proposed model results in a fuzzy multi-objective non-linear programming, we present a solution procedure based on a modification of fuzzy parametric programming (FPP) and minimum deviation method. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： Multi-criteria data envelopment analysis Location-allocation problem fuzzy parametric programming Minimum deviation method

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A mathematical programming approach for measuring technical efficiency in a fuzzy environment

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JOURNAL OF PRODUCTIVITY ANALYSIS 1998年第1期10卷 85-102页

作者： Triantis, K Girod, O Virginia Tech No Virginia Ctr Coll Engn Falls Church VA 22043 USA

A three stage approach is proposed to measure technical efficiency in a fuzzy environment. This approach uses the traditional data envelopment analysis framework and then merges concepts developed in fuzzy parametric programming (Carlsson and Korhonen, 1986), In the first stage, vague input and output variables are expressed in terms of their risk-free and impossible bounds and a membership function. This membership function represents the degree to which a production scenario is plausible, In the second stage, conventional efficiency measurement models (Banker, Charnes and Cooper, 1984;Deprins, Simar and Tulkens, 1984) are re-formulated in terms of the risk-free and impossible bounds and the membership function for each of the fuzzy input and output variables, In the third stage, technical efficiency scores are computed for different values of the membership function so as to identify uniquely sensitive decision making units, The approach is illustrated in the context of a preprint and packaging manufacturing line which inserts commercial pamphlets into newspapers.

关键词： technical efficiency fuzzy parametric programming fuzzy data envelopment analysis fuzzy free disposal hull

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