A multi-objective programming problem and its equivalent goal programming problem with appropriate priorities and aspiration levels: A fuzzy approach

Mohanty, B. K.; Vijayaraghavan, T.A.S.

doi:10.1016/0305-0548(94)00066-h

Cited by 31 publications

(9 citation statements)

References 9 publications

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“…(1986, 1987) have investigated a particular modelling in the FGP by introducing the preemptive priority structure and weights by employing the usual addition as an operator to aggregate the fuzzy goals. Mohanty and Vijayaraghavan (1995) have proposed an approach to convert a MOP problem into a Lexicographic GP by using the concept of fuzzy sets to address an urban scheduling problem. The authors raised an important issue, which related to the fact that the DM may have some difficulties to fix easily the priority levels of the objectives.…”

Section: Lexicographic Fgpmentioning

confidence: 99%

“…Mohanty and Vijayaraghavan (1995) have addressed an urban vehicle scheduling problem where a set of fixed routes and types of vehicles are considered. They consider the following objectives: operating cost, the vehicle utilization, and the operating revenue.…”

Section: Some Applications Of Fgp In Management and Economicsmentioning

confidence: 99%

“…To solve their model, the authors have used the Cohon's (1978) procedure of gradients of the objectives to determine the regions of conflict, which implies a pair‐wise comparison between objectives. Then, a symmetric matrix describing the degree of nonconflict between objectives is established with the objective to facilitate fixing the priorities and the aspiration levels (Mohanty and Vijayaraghavan, 1995). Finally, the usual Lexicographic GP model is used to solve the rest of the problem.…”

Section: Some Applications Of Fgp In Management and Economicsmentioning

confidence: 99%

See 2 more Smart Citations

Fuzzy goal programming model: an overview of the current state‐of‐the art

Aouni

Martel

Hassaine

2009

Multi Criteria Decision Anal

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The standard Goal Programming (GP) model considers the aspiration levels (goals) as precise and deterministic. However, in practice, there are many decision-making situations where the decision-maker is not able to establish the goal values precisely. The goals fuzziness is more related to the nature of the objectives involved in the decisionmaking situation. The Fuzzy Goal Programming (FGP) Model has been developed in the earliest of the 80s to deal with such situations. The concept of membership functions, based on fuzzy sets theory, has been used for modelling the goals fuzziness in the GP. The aim of this paper is to give an overview of the current state-of-the art regarding the FGP model.

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Section: Lexicographic Fgpmentioning

confidence: 99%

Section: Some Applications Of Fgp In Management and Economicsmentioning

confidence: 99%

Section: Some Applications Of Fgp In Management and Economicsmentioning

confidence: 99%

See 1 more Smart Citation

Fuzzy goal programming model: an overview of the current state‐of‐the art

Aouni

Martel

Hassaine

2009

Multi Criteria Decision Anal

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“…The concept of fuzzy numbers is introduced to treat imprecise data, such as the processing time of each job. Introducing fuzzy numbers, the ALB problem can be solved as Fuzzy Binary Linear Programming problem [4,5,8,11,12,14]. This study proposes an algorithm that can simultaneously solve a BLP problem with fuzzy coefficients in the objective function and in a constraints.…”

Section: Introductionmentioning

confidence: 99%

Solving type-2 assembly line balancing problem with fuzzy binary linear programming

Scalia

2013

Journal of Intelligent &Amp; Fuzzy Systems

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This paper deals with the use of fuzzy set theory as a viable alternative method for modelling and solving the stochastic assembly line balancing problem. This paper presents a fuzzy extension of the simple assembly line balancing problem of type 2 (SALBP-2) with fuzzy job processing times since uncertainty, variability, and imprecision are often occurred in real-world production systems. The job processing times are formulated by triangular fuzzy membership functions using their statistical distributions. This study proposes to solve a Fuzzy Binary Linear Problem (FBLP) with fuzzy coefficients in the objective function and in a constraint. Finally, the effect of the unbalancing of a station in a real case study has been investigated in order to consider different scenarios. In particular, four different scenarios were studied considering the balanced and unbalanced line with deterministic and stochastic job processing times. The results obtained showed that the use of a fuzzy approach allows to take in account the effect of the job processing time variability demonstrating the validity of the proposed model.

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“…By considering the concepts of multiple-attribute decision-making, we have highlighted this case in the Internet market. The multi-attribute approach is one of the many models that have been developed to deal with the decision-making situations where several factors such as objectives, constraints, or attributes have to be considered simultaneously (Aouni and Kettani, 2001;Carlsson and Fuller, 1996;Martel and Aouni, 1998;Mohanty, 1998;Mohanty and Vijayaraghvan, 1995;Triantaphyllou, 2000). The proposed procedure could be qualified as a decision aid tool since it enables the customer to get more involved in the decision-making process.…”

Section: Introductionmentioning

confidence: 99%

Product selection in Internet business: a fuzzy approach

Mohanty

Aouni

2010

Int Trans Operational Res

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In this paper, we propose a methodology which helps customers buy products through the Internet. This procedure takes into account the customer's level of desire in the product attributes, which are normally fuzzy, or in linguistically defined terms. The concept of fuzzy number will be used to measure the degree of similarities of the available products to that of the customer's requirements. The degrees of similarities so obtained over all the attributes give rise to the fuzzy probabilities and hence the fuzzy expected values of availing a product on the Internet as per the customer's requirement. Attribute‐wise the fuzzy expected values are compared with those of the available products on the Internet and the product that is closest to the customer's preference is selected as the best product. The multi‐attribute weighted average method is used here to evaluate and hence to select the best product.

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A multi-objective programming problem and its equivalent goal programming problem with appropriate priorities and aspiration levels: A fuzzy approach

Cited by 31 publications

References 9 publications

Fuzzy goal programming model: an overview of the current state‐of‐the art

Fuzzy goal programming model: an overview of the current state‐of‐the art

Solving type-2 assembly line balancing problem with fuzzy binary linear programming

Product selection in Internet business: a fuzzy approach

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