A fuzzy goal programming method with imprecise goal hierarchy

Aköz, Onur; Petrov́ić, Dobrila

doi:10.1016/j.ejor.2005.11.049

Cited by 68 publications

(59 citation statements)

References 14 publications

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“…From a computer search in the SCOPUS and ABI/Inform Global conducted to collect the relevant studies using and/or citing Romero's unifying framework, a total of 28 scientific papers citing Romero's approach can be found. Bal et al (2006), Yaghoobi and Tamiz (2007), Chang (2007), Yaghoobi et al (2008) and Aköz and Petrovic (2007) among others, present some interesting recent theoretical extensions of Romero's unifying theories. Several case studies and real applications could also be found citing Romero's model, e.g.…”

Section: A Fuzzy Extended Lexicographic Goal Programmingmentioning

confidence: 96%

A new approach of Romero’s extended lexicographic goal programming: fuzzy extended lexicographic goal programming

et al. 2009

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Goal programming (GP) is perhaps one of the most widely used approaches in the field of multicriteria decision making. The major advantage of the GP model is its great flexibility which enables the decision maker to easily incorporate numerous variations on constraints and goals. Romero provides a general structure, extended lexicographic goal programming (ELGP) for GP and some multiobjective programming approaches. In this work, we propose the extension of this unifying framework to fuzzy multiobjective programming. Our extension is carried out by several methodologies developed by the authors in the fuzzy GP approach. An interval GP model has been constructed where the feasible set has been defined by means of a relationship between fuzzy numbers. We will apply this model to our fuzzy extended lexicographic goal programming (FELGP). The FELGP is a general primary structure with the same advantages as Romero's ELGP and moreover it has the capacity of working with imprecise information. An example is given in order to illustrate the proposed method.

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Section: A Fuzzy Extended Lexicographic Goal Programmingmentioning

confidence: 96%

A new approach of Romero’s extended lexicographic goal programming: fuzzy extended lexicographic goal programming

et al. 2009

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“…Accordingly, if µ A (x) =1, then x is located in A, and if µ A (x) =0, x is not member of A. So, fuzzy sets and their membership functions are generalization of crisp functions (Akoz and Petrovic, 2007).…”

Section: Membership Function Of Fuzzy Setsmentioning

confidence: 99%

Optimization Production Planning Using Fuzzy Goal Programming Techniques

Taghizadeh¹,

Bazrkar²,

Abedzadeh³

2015

MAS

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In the past two decades, ideal planning has been used for the multiple criteria decision making problem solving. The issue is raised here is that how to do a program to achieve the best and most comprehensive program that it has well run ability? Because of costly medical equipment production process, it should pay more attention to production planning. In this research, this was carried out in the company's beta; we are looking to fulfill two objectives, reducing the cost of production, increase revenue leading to increased profits. For the realization of these goals, we use the method of fuzzy planning, according to studies, we use simple collective models and collective weighted method. According to the existing information and problem variables and TIVARY model, we find that the model leads to production costs and increasing income. According to the results of the research, we realized that for the realization of the Beta purposes, we should use TIVARY collective method. This study has expanded the discussion of optimization production planning using fuzzy goal programming techniques. Goal programming was used in various issues such as decision making. The most important goal programming restrictions is unclear goals. Fuzzy goal programming provided, it investigate fuzzy purpose in unknown level.

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“…The fuzzy goal programming approach is one of the best useful tools in confronting such problems. Applying fuzzy set theory in goal programming (GP) has the advantage that allows the decision maker to define imprecise aspiration levels [20,21]. To find the optimal solution of multiobjective problems, several methods have been introduced, such as weighted metric, weighted sum, -constraint, interactive approaches, and fuzzy goal programming (FGP).…”

Section: Fuzzy Goal Programming Modelmentioning

confidence: 99%

“…Also, a fuzzy goal programming method with ambiguous goal hierarchy was studied by Aköz and Petrovic [20]. Iskander [23] employed a fuzzy weighted increasable approach.…”

Section: Fuzzy Goal Programming Modelmentioning

confidence: 99%

Satisfying the Energy Demand of a Rural Area by Considering the Investment on Renewable Energy Alternatives and Depreciation Costs

Rabbani

Rahimi

Kazemi

et al. 2014

Journal of Renewable Energy

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In this paper, a fuzzy multiobjective model which chooses the best mix of renewable energy options and determines the optimal amount of energy to be transferred from each resource to each end use is proposed. The depreciation of equipment along with time value of money has been taken into account in the first objective function while the second and the third objective functions minimize the greenhouse gas emissions and water consumption, respectively. Also, this study is one of the pioneer works that has considered demand-side management (DSM) as a competitive option against supply-side alternatives for making apt energy planning decisions. Moreover, the intrinsic uncertainty of demand parameter is considered and modeled by fuzzy numbers. To convert the proposed fuzzy multiobjective formulation to a crisp single-objective formulation the well-known fuzzy goal programming approach together with Jimenez defuzzifying technique is employed. The model is validated through setting up a diversity of datasets whose data were mostly derived from the literature. The obtained results show that DSM programs have greatly contributed to cost reductions in the network. Also, it is concluded that the model is capable of solving even large-scaled instances of problems in negligible central processing unit (CPU) times using Lingo 8.0 software.

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A fuzzy goal programming method with imprecise goal hierarchy

Cited by 68 publications

References 14 publications

A new approach of Romero’s extended lexicographic goal programming: fuzzy extended lexicographic goal programming

A new approach of Romero’s extended lexicographic goal programming: fuzzy extended lexicographic goal programming

Optimization Production Planning Using Fuzzy Goal Programming Techniques

Satisfying the Energy Demand of a Rural Area by Considering the Investment on Renewable Energy Alternatives and Depreciation Costs

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