• Industrial Engineering and Management Systems
• /
• 제3권2호
• /
• pp.116-122
• /
• 2004

This paper presents a process plan selection model with multiple objectives. The process plans for all parts should be selected under multiple objective environment as follows: (1) minimizing the sum of machine processing and material handling time of all the parts considering realistic shop factors such as production volume, processing time, machine capacity, and capacity of transfer device. (2) balancing the load between machines. A multiple objective mathematical model is proposed and an evolutionary algorithm with the adaptive recombination strategy is developed to solve the model. To illustrate the efficiency of proposed approach, numerical examples are presented. The proposed approach is found to be effective in offering a set of satisfactory Pareto solutions within a satisfactory CPU time in a multiple objective environment.

• Management Science and Financial Engineering
• /
• 제20권1호
• /
• pp.1-9
• /
• 2014

In multi-objective scheduling problems, the objectives are usually in conflict. To obtain a satisfactory compromise and resolve the issue of NP-hardness, most existing works have suggested employing meta-heuristic methods, such as genetic algorithms. In this research, we propose a novel data-driven approach for generating a single solution that compromises multiple rules pursuing different objectives. The proposed method uses a data mining technique, namely, random forests, in order to extract the logics of several historic schedules and aggregate those. Since it involves learning predictive models, future schedules with the same previous objectives can be easily and quickly obtained by applying new production data into the models. The proposed approach is illustrated with a simulation study, where it appears to successfully produce a new solution showing balanced scheduling performances.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 1998년도 추계학술대회 학술발표 논문집
• /
• pp.211-217
• /
• 1998

Many practical control problems for the complex, uncertain or large-scale plants, need to simultaneously achieve a number of objectives, which may conflict or compete with each other. If the conventional optimization methods are applied to solve these control problems, the solution process may be time-consuming and the resulting solution would ofter lose its original meaning of optimality. Nevertheless, the human operators usually performs satisfactory results based on their qualitative and heuristic knowledge. In this paper, we investigate the control strategies of the human operators, and propose a fuzzy model-based multi-objective satisfactory controller. We also apply it to the automatic train operation(ATO) system for the magnetically levitated vehicles(MAGLEV). One of the human operator's strategies is to predict the control result in order to find the meaningful solution. In this paper, Takagi-Sugeno fuzzy model is used to simulated the prediction procedure. Another str tegy is to evaluate the multiple objectives with respect to their own standards. To realize this strategy, we propose the concept of a satisfactory solution and a satisfactory control scheme. The MAGLEV train is a typical example of the uncertain, complex and large-scale plants. Moreover, the ATO system has to satisfy multiple objectives, such as seed pattern tracking, stop gap accuracy, safety and riding comfort. In this paper, the speed pattern tracking controller and the automatic stop controller of the ATO system is designed based on the proposed control scheme. The effectiveness of the ATO system based on the proposed scheme is shown by the experiments with a rotary test bed and a real MAGLEV train.

• 한국항공우주학회지
• /
• 제31권6호
• /
• pp.61-71
• /
• 2003

터보제트엔진 모델에 대한 제어에 있어서, 비교적 잘 설계된 PI 제어기 성능결과를 바탕으로 Takagi-Sugeno형 뉴로-퍼지 추론계를 통한 플랜트 모델의 제어 시스템을 규명함으로서, PI형 T-S 퍼지규칙들을 퍼지제어기를 설계하였다. 이렇게 설계된 제어기의 성능을 향상시키기 위하여, 각 퍼지규칙들을 퍼지 C-Means Algorithm으로부터 각각의 목적 함수군으로 분류한 후, 각 분류군에 대해 규칙간의 가중치가 각 목적함수의 만족도에 부합되도록 하는 기법을 제시하였고, 이를 잘 설계된 T-S형 퍼지제어기에 적용하여 성능을 향상시킴으로써 그 유용성을 보였다.

• 대한산업공학회지
• /
• 제14권1호
• /
• pp.119-131
• /
• 1988

Vehicle Scheduling Problem (VSP) is a generic name given to a whole class of problems involving the visiting of "stations" by "vehicles," where a time is associated with each activity. The studies performed to date have the common feature of a single objective while satisfying a set of restrictions and known customer supplies or demands. However, VSPs may involve relevant multiple objectives and probabilistic supplies or demands at stations, creating multicriteria stochastic VSPs. This paper proposes a heuristic algorithm based on goal programming approach to schedule the most satisfactory vehicle routes of a bicriteria VSP with probabilistic supplies at stations. The two relevant objectives are the minimization of the expected travel distance of vehicles and the minimization of the due time violation for collection service at stations by vehicles. The algorithm developed consists of three major stages. In the first stage, an artificial capacity of vehicle is determined, on the basis of decision maker's subjective estimates. The second one clusters a set of stations into subsets by applying an efficient cluster method developed. In the third one, the stations in each subset are scheduled by applying an iterative goal programming heuristic procedure to each cluster.

• 한국환경보건학회지
• /
• 제38권6호
• /
• pp.550-560
• /
• 2012

Objectives: QSAR methodology was applied to explain two different sets of acceptable daily intake (ADI) data of 74 pesticides proposed by both the USEPA and WHO in terms of setting guidelines for food and drinking water. Methods: A subset of calculated descriptors was selected from Dragon$^{(R)}$ software. QSARs were then developed utilizing a statistical technique, genetic algorithm-multiple linear regression (GA-MLR). The differences in each specific model in the prediction of the ADI of the pesticides were discussed. Results: The stepwise multiple linear regression analysis resulted in a statistically significant QSAR model with five descriptors. Resultant QSAR models were robust, showing good utility across multiple classes of pesticide compounds. The applicability domain was also defined. The proposed models were robust and satisfactory. Conclusions: The QSAR model could be a feasible and effective tool for predicting ADI and for the comparison of logADIEPA to logADIWHO. The statistical results agree with the fact that USEPA focuses on more subtle endpoints than does WHO.

• 한국경영과학회:학술대회논문집
• /
• 대한산업공학회/한국경영과학회 1994년도 춘계공동학술대회논문집; 창원대학교; 08월 09일 Apr. 1994
• /
• pp.103-111
• /
• 1994

An interactive and iterative design method based on the constraint satisfaction problem (CSP) technique was developed to generate an ergonomically sound layout of a control panel. This control panel layout method attempts to incorporate a variety of relevant ergonomic principles and design constraints, and generate an optimal or, at least, a "satisfactory" solution through iterative interactions with the designer. The existing panel design and layout methods are mostly based on the optimization of single objective function formulated to reflect and trade off all ergonomic design objectives which are largely different in their nature. In fact, the problem of seeking an ergonomically sound panel design should be viewed as a multiple objective optimization problem. Furthermore, most of the design objectives should be understood as constraints rather than objectives to be optimized. Hence, a constraint satisfaction approach is proposed in this study as a framework for the panel designer to search through the design decision space effectively and make various design decisions iteratively. In order to apply the constraint satisfaction approach to the panel design procedure, the ergonomic principles such as frequency-of-use, importance, functional grouping, and sequence-of-use are formalized as CSP terms. With this formalization, a prototype system was implemented and applied to panel layout problems. The results clearly showed the effectiveness of the proposed approach since it permits designers to consider and iteratively evaluate various design constraints and ergonomic principles, and, therefore, aids the panel designer to come up with an ergonomically sound control panel layout.

• 국제학술발표논문집
• /
• The 2th International Conference on Construction Engineering and Project Management
• /
• pp.642-652
• /
• 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.

• 대한인간공학회:학술대회논문집
• /
• 대한인간공학회 1994년도 춘계학술대회논문집
• /
• pp.75-84
• /
• 1994

A control panel layout method based on the constraint satisfaction problem(CSP) technique was developed to generate an ergonomically sound panel design. This control panel layout method attempts to incorporate a variety of relevant ergonomic principles and design constrains, and generate an optimal or, at least, a "satisfactory" solution through the efficient search algorithm. The problem of seeking an ergonomically sound panel design should be viewed as a multiple criteria problem, and most of the design objectives should be understood as constraints. Hence, a CSP technique was employed in this study for dealing with the multi-constraiants layout problem. The efficient search algorithm using "preprocess" and "look ahead" procedures was developed to handle the vast amount of computational effort. In order to apply the CSP technique to the panel layout procedure, the ergonomic principles such as spatial compatibility, frequency-of- use, importance, functional grouping, and sequence-of-use were formalized as CSP terms. The effectiveness of the developed panel layout method was evaluated by example problems, and the results clearly showed that the generated layouts took various ergonomic design principles into account.esign principles into account.

• 한국치위생학회지
• /
• 제18권5호
• /
• pp.751-761
• /
• 2018

Objectives: The purpose of this study was to identify factors affecting choice of treatment hospital (i.e., determinants) and satisfaction with the treatment hospital, and to provide a more satisfactory and high-quality medical service for orthodontic patients. Methods: A questionnaire survey was conducted for approximately 1 month beginning in August 2017, involving patients who visited orthodontic dentistry clinics in Seoul and Gyeonggi-do. Multiple regression analysis was performed on the results to examine factors that affected satisfaction with orthodontic treatment. Results: The determinant of dental clinics was 3.90 points overall; hospital environment and facilities were highest at 4.05, followed by dental hygienist at 3.99, and dentist at 3.97. Factors influencing satisfaction with orthodontic treatment were positively influenced by dentists (p<0.01), medical procedures (p<0.01) and medical expenses (p<0.01). Conclusions: It is important to provide comfort and convenience to patients by simplifying hospital facility management, reception, and reservation procedures.