• Journal of applied mathematics & informatics
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• v.12 no.1_2
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• pp.251-260
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• 2003

Generally, in deriving the solution of economic production quantity (EPQ) inventory model, we consider the demand rate and deterioration rate as constant quantity. But in case of real life problems, the demand rate and deterioration rate are not actually constant but slightly disturbed from their original crisp value. The motivation of this paper is to consider a more realistic EPQ inventory model with finite production rate, fuzzy demand rate and fuzzy deterioration rate. The effect of the loss in production quantity due to faulty/old machine have also been taken into consideration. The methodology to obtain the optimum value of the fuzzy total cost is derived and a numerical example is used to illustrate the computation procedure. A sensitivity analysis is also carried out to get the sensitiveness of the tolarance of different input parameters.

• International conference on construction engineering and project management
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• 2007.03a
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• pp.642-652
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• 2007

Many contracting firms and project managers in the construction industry have started to utilize multi objective optimization methods to handle multiple conflicting goals for completing the project within the stipulated time and budget with required quality and safety. These optimization methods have increased the pressure on decision makers to search for an optimal resources utilization plan that optimizes simultaneously the total project cost, completion time, and crashing cost by considering indirect cost, contractual penalty cost etc., practically charging them in terms of direct cost of the project which is fuzzy in nature. This paper presents a multiple fuzzy goal programming model (MFGP) that supports decision makers in performing the challenging task. The model incorporates the fuzziness which stems from the imprecise aspiration levels attained by the decision maker to these objectives that are quantified through fuzzy linear membership function. The membership values of these objectives are then maximized which forms the fuzzy decision. The problem is solved using LINGO 8 optimization solver and the best compromise solution is identified. Comparison between solutions of MFGP, fuzzy multi objective linear programming (FMOLP) and multiple goal programming (MGP) are also presented. Additionally, an interactive decision making process is developed to enable the decision maker to interact with the system in modifying the fuzzy data and model parameters until a satisfactory solution is obtained. A case study is considered to demonstrate the feasibility of the proposed model for optimization of project network parameters in the construction industry.

• International conference on construction engineering and project management
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• 2007.03a
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• pp.69-78
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• 2007

In real world, the project managers handle conflicting goals that govern the use of resources within the stipulated time and budget with required quality and safety. These conflicting goals are required to be optimized simultaneously by the project managers in the framework of fuzzy aspiration levels. The fuzzy linear programming model proposed herein helps project managers to minimize total project costs, completion time, and crashing costs considering indirect costs, contractual penalty costs etc by practically charging them in terms of direct cost of the project. A case study of bituminous pavement under construction is considered to demonstrate the feasibility of applying the proposed model for optimization of project parameters. Consequently, the proposed model yields an efficient compromise solution and the decision maker's overall degree of satisfaction with multiple fuzzy goal values. Additionally, the proposed model provides a systematic decision-making framework, enabling decision maker to interactively modify the fuzzy data and model parameters until a satisfactory solution is obtained. The significant characteristics that differentiate the proposed model with other models include, flexible decision-making process, multiple objective functions, and wide-ranging decision information.

• International Journal of Reliability and Applications
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• v.12 no.2
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• pp.79-94
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• 2011

Redundancy-reliability allocation problems in multi-stage series-parallel systems are addressed in this study. Fuzzy programming techniques are proposed for finding satisfactory solutions. First, a multi-objective programming model is formulated for simultaneously maximizing system reliability and minimizing system total cost. Due to the nature of uncertainty in the problem, the fuzzy set theory and technique are used to convert the deterministic multi-objective programming model into a fuzzy nonlinear programming problem. A heuristic method is developed to get satisfactory solutions for the fuzzy nonlinear programming problem. A Pareto optimal solution is found with maximal degree of satisfaction from the interception area of fuzzy sets. A case study that is related to the electronic control unit installed on aircraft engine over-speed protection system is used to implement the developed approach. Results suggest that the developed fuzzy multi-objective programming model can effectively resolve the fuzzy and uncertain problem when design goals and constraints are not clearly confirmed at the initial conceptual design phase.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.34
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• pp.185-191
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• 1995

In this research, a mathematical programming model is developed for the economic modeling of sampling plans based on two evaluation criteria : the outgoing quality and the average total inspection cost A fuzzy goal programming model and its solution procedure are proposed for the managers whose management objectives on the two evaluation criteria are not rigorous. To study the sensitivity of quality characteristic dependence on the resulting inspection plans, a numerical example is solved several times for a dependent model.

• Proceedings of the KIEE Conference
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• 2004.11b
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• pp.261-265
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• 2004

This paper proposes a fuzzy dual method for analyzing long-term transmission system expansion planning problem considering ambiguities of the power system using fuzzy lineal programming. Transmission expansion planning problem can be formulated integer programming or linear programming with minimization total cost subject to reliability (load balance). A long-term expansion planning problem of a grid is very complex, which have uncertainties fur budget, reliability criteria and construction time. Too much computation time is asked for actual system. Fuzzy set theory can be used efficiently in order to consider ambiguity of the investment budget (economics) for constructing the new transmission lines and the delivery marginal rate (reliability criteria) of the system in this paper. This paper presents formulation of fuzzy dual method as first step for developing a fuzzy Ford-Fulkerson algorithm in future and demonstrates sample study. In application study, firstly, a case study using fuzzy integer programming with branch and bound method is presented for practical system. Secondly, the other case study with crisp Ford Fulkerson is presented.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.7
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• pp.313-317
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• 2001

This paper proposed a fuzzy logic cross coupled controller which can enhance the path tracking performance of optically guided AGV(Automated Guided Vehicle). The AGV follows the guide path, it cannot be avoid the deviation from the path due to the inevitable error and the deviation must be corrected. Optically guided AGV used in industrial area is controlled by On-Off controller generally, the experimental AGV has three optical sensors in front body. In this structure, we could not know the leaving distance accurately and steering angle from the guided line, so AGV could not be controlled properly with conventional controller in the case of increasing or decreasing velocity. If we mount additional sensors the AGV, we could know the leaving distance and steering angle from the guided line and proper error compensating methode can be applied. But because cost of sensors are high, the cost of total system is increasing. So, in this paper, to improve the tracking performance of AGV which has the minimum number of sensors and fuzzy logic cross coupled controller is proposed. Some simulations and experimental results are presented to illustrate the performance of the proposed controller.

• Journal of Electrical Engineering and Technology
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• v.12 no.4
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• pp.1511-1518
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• 2017

Renewable energy hybrid systems look into the process of choosing the finest arrangement of components and their sizing with suitable operation approach to deliver effective, consistent and cost effective energy source. This paper presents hybrid renewable energy system (HRES) solar photovoltaic, downdraft biomass gasifier, and fuel cell based generation system. HRES electrical power to supply the electrical load demand of academic research building sited in $23^{\circ}12^{\prime}N$ latitude and $77^{\circ}24^{\prime}E$ longitude, India. Fuzzy logic programming discover the most effective capital and replacement value on components of HRES. The cause regarding fuzzy logic rule usage on HOMER pro (Hybrid optimization model for multiple energy resources) software program finds the optimum performance of HRES. HRES is designed as well as simulated to average energy demand 56.52 kWh/day with a peak energy demand 4.4 kW. The results shows the fuel cell and battery bank are the most significant modules of the HRES to meet load demand at late night and early morning hours. The total power generation of HRES is 23,794 kWh/year to the supply of the load demand is 20,631 kWh/year with 0% capacity shortage.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.61
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• pp.41-50
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• 2000

Cell formation(CF) Is to group parts with similar geometry, function, material and process into part families, and the corresponding machines into machine cells. Cell formation solutions often contain exceptional elements(EEs). Also, the following objective functions - minimizing the total costs of dealing with exceptional elements and maximizing total similarity coefficients between parts - have been used in CF modeling. Thus, multiobjective programming approach can be developed to model cell formation problems with two conflicting objective functions. This paper presents an effective cell formation method with fuzzy multiobjective nonlinear mixed-integer programming simultaneously to form machine cells and to minimize the cost of eliminating EEs.

• Journal of Korea Port Economic Association
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• v.37 no.4
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• pp.13-31
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• 2021

Since the signing of the Korea-Europe Free Trade Agreement, the volume of trade transactions between South Korea and Europe has increased. The traditional single-mode transport system has been transformed into an intermodal transport system using two or more modes of transport. In addition, the conventional sea and air transport routes have been restricted, leading to a decline in Korean exports to Europe, and the rail transport mode is becoming mainstream in the market due to the influence of COVID-19. This paper focuses on the China-Railway Express to explore a new intermodal transport route from Korea to Europe. First, the fuzzy analytic hierarchy process (AHP) is used to evaluate the factor weights when selecting intermodal transport routes from Korea to Europe. Then, the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method is used to rank three alternatives. The results show that among the four factors (total cost, total time, transportation capability, and service reliability), the total cost is the most significant factor, followed by the total time, service reliability, and transportation capability. Furthermore, the alternative route 1 (Incheon-Dalian-Manchuria-Hamburg) is preferred.