• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.45
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• pp.11-23
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• 1998

This paper presents a more efficient evaluation of alternatives by use of multi-criteria decision making methodlogy under fuzzy intersectional dependence relations. The performance evaluation of most systems such as weapons, enterprise systems etc. are multiple criteria decision making problems. The descriptions and judgements on these systems are usually linguistic and fuzzy. The traditional methods of Analytic Hierarchy Process(AHP) are mainly used in crisp(non-fuzzy) decision applications with a very unbalanced scale of judgements and rank reversal. To overcome these problems, we will propose a new, general decision making method for evaluation models using fuzzy AHP(FAHP) under fuzzy intersectional dependence relations. The T.M.S alternatives A, B and C will be evaluted by the Fuzzy Analytic Hierachy Process (FAHP) based on entropy weight in this study. We will use symmetric triangular fuzzy numbers to indicate the relative strength of the elements in the hierachy and degree of intersection between criteria. These problems are evaluated by five criteria : tactical criteria, technology criteria, maintenance criteria, economy criteria, advacement criteria.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.223-227
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• 2021

A treatment based on the algebraic operations on fuzzy numbers is used to replace the fuzzy problem into an equivalent crisp one. The finite difference technique is used to replace the continuous boundary value problem (BVP) of arbitrary order 1<α≤2, with fuzzy boundary parameters into an equivalent crisp (algebraic or differential) system. Three numerical examples with different behaviors are considered to illustrate the treatment of the singular perturbed case with different fractional orders of the BVP (α=1.8, α=1.9) as well as the classical second order (α=2). The calculated fuzzy solutions are compared with the crisp solutions of the singular perturbed BVP using triangular membership function (r-cut representation in parametric form) for different values of the singular perturbed parameter (ε=0.8, ε=0.9, ε=1.0). Results are illustrated graphically for the different values of the included parameters.

• Journal of the Korean Institute of Navigation
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• v.20 no.4
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• pp.59-70
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• 1996

A berth assignment problem has a direct impact on assessment of charges made to ships and goods. In this paper, we concerned with of fuzzy mathematical programming models for a berth assignment problem to achieved an efficient berth operation in a fuzzy environment. In this paper, we focus on the berth assignment programming with fuzzy parameters which are based on personal opinions or subjective judgement. From the above point of view, assume that a goal and a constraint are given by fuzzy sets, respectively, which are characterized by membership functions. Let a fuzzy decision be defined as the fuzzy set resulting from the intersection of a goal and constraint. This paper deals with fuzziness in all parameters which are expressed by fuzzy numbers. A fuzzy parameter defined by a fuzzy number means a possibility distribution of the parameters. These fuzzy 0-1 integer programming problems are formulated by fuzzy functions whose concept is also called the extension principle. We deal with a berth assignment problem with triangular fuzzy coefficients and propose a branch and bound algorithm for solving the problem. We suggest three models of berth assignment to minimizing the objective functions such as total port time, total berthing time and maximum berthing time by using a revised Maximum Position Shift(MPS) concept. The berth assignment problem is formulated by min-max and fuzzy 0-1 integer programming. Finally, we gave the numerical solutions of the illustrative examples.

• Journal of the Korean Operations Research and Management Science Society
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• v.13 no.2
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• pp.163-163
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• 1988

This research shows that fuzzy set theory can be useful in modeling and solving flow shop scheduling problems with uncertain processing times and illustrates a method for solving job sequencing problem which the opinions of experts disagree in each processing time. In this study, FCDS (Fuzzified Campbell-Dudek-Smith) algorithm and FNEH (Fuzzified Nawaz-Enscope-Ham) algorithm are proposed to improve the fuzzified Branch & Bound algorithm that requires long run-time and computational complexities to find the optimal sequence. These proposed algorithms are also designed to treat opinions of experts. In this paper, Fuzzy processing times are expressed as triangular fuzzy numbers and comparison method use Lee-Li method and ranking method based on the dominance property. On the basis of the proposed method, an example is presented.

• Korean Management Science Review
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• v.13 no.2
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• pp.163-175
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• 1996

This research shows that fuzzy set theory can be useful in modeling and solving flow shop scheduling problems with uncertain processing times and illustrates a method for solving job sequencing problem which the opinions of experts disagree in each processing time. In this study, FCDS (Fuzzified Campbell-Dudek-Smith) algorithm and FNEH (Fuzzified Nawaz-Enscope-Ham) algorithm are proposed to improve the fuzzified Branch & Bound algorithm that requires long run-time and computational complexities to find the optimal sequence. These proposed algorithms are also designed to treat opinions of experts. In this paper, Fuzzy processing times are expressed as triangular fuzzy numbers and comparison method use Lee-Li method and ranking method based on the dominance property. On the basis of the proposed method, an example is presented.

• Journal of applied mathematics & informatics
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• v.31 no.1_2
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• pp.99-110
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• 2013

In this article, sensitivity analysis of atmospheric dispersion model RIMPUFF is considered. Uncertain parameters are taken to be triangular fuzzy numbers, and sensitivity analysis is carried out by using the Hartley-like measure. Codes for evaluating membership function using the Vertex method and the Hartley-like measure are prepared using Matlab.

• Industrial Engineering and Management Systems
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• v.15 no.4
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• pp.364-373
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• 2016

Disassembly is one of the important activities in treating with the product at the End of Life time (EOL). Disassembly is defined as a systematic technique in dividing the products into its constituent elements, segments, sub-assemblies, and other groups. We concern with a Fuzzy Disassembly Line Balancing Problem (FDLBP) with multiple objectives in this article that it needs to allocation of disassembly tasks to the ordered group of disassembly Work Stations. Tasks-processing times are fuzzy numbers with triangular membership functions. Four objectives are acquired that include: (1) Minimization of number of disassembly work stations; (2) Minimization of sum of idle time periods from all work stations by ensuring from similar idle time at any work-station; (3) Maximization of preference in removal the hazardous parts at the shortest possible time; and (4) Maximization of preference in removal the high-demand parts before low-demand parts. This suggested model was initially solved by GAMS software and then using Genetic Algorithm (GA) in MATLAB software. This model has been utilized to balance automotive engine disassembly line in fuzzy environment. The fuzzy results derived from two software programs have been compared by ranking technique using mean and fuzzy dispersion with each other. The result of this comparison shows that genetic algorithm and solving it by MATLAB may be assumed as an efficient solution and effective algorithm to solve FDLBP in terms of quality of solution and determination of optimal sequence.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.30 no.1
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• pp.89-95
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• 2007

In general, reliability of AHP(Analytic Hierarchy Process) depends on pairwise comparison of evaluators. In addition, human judgment on the importance of alternatives or criteria is always imprecise and vague. To cope with these shortcomings, Fuzzy AHP is suggested and used widely recently. But in Fuzzy AHP, it cannot deal with the evaluator's various attitudes towards risk and confidence owing to evaluator's different expertise and experience. This paper proposes a method for consideration of evaluator's confidence and risk attitude in Fuzzy AHP. And suggested methods are applied various scenarios to verify the meaningfulness. The result shows that the priority of alternatives can be change through the consideration of evaluator's confidence and risk attitude.

• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.1
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• pp.139-157
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• 1993

This paper presents possibilistic job scheduling based on the membership function as an alternative to probabilistic job scheduling and illustrates a methodology for solving job sequencing problem which the opinions of experts greatly disagree in each processing time. Triangular fuzzy numbers are used to represent the processing times of experts. Here, the comparison method is based on the dominance property. The criteria for dominance are presented. By the dominance criteria, for each job, a mojor TFN and a minor TFN are selected and apessimistic sequence with mojor TFNs and an optimistic sequence with minor TFNs are computed. The three-machine flow shop problem is considered as an example to illustrate the approach.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.2
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• pp.70-78
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• 1997

Proportional-integral-derivative(P1D) controllers have been still widely used in industrial processes due to their simplicity, effectiveness, robustness for a wide range of operating conditions, and the familiarity of control engineers. And a number of recent papers in fuzzy systems are showing that fuzzy systems are universal approximators. That is, fuzzy controllers are capable of approximating any real continuous function on a compact set of arbitrary accuracy. In this paper, we derive the linear PID control law from the fuzzy control algorithm where all fuzzy sets for representing plant state variables and a control variable use common triangular types. We first lead a linear PD control law from a fuzzy logic control with only two fuzzy sets for error and change-of-error. And then we derive the linear PID control law from a fuzzy controller. We here assumed that the intervals of error, change-of-error, and integral error could be partitioned into arbitrary numbers, respectively. As a result, a linear PID controller is only a sort of various fuzzy logic controls.