This paper shows the application of fuzzy set and nonlinear membership function to linear programming problems in a fuzzy environment. In contrast to typical linear programming problems, the objectives and constraints of the problem in a fuzzy environment are defined imprecisely. This paper describes that fuzzy linear programming models can be formulated using the basic concepts of membership functions and fuzzy sets, and that they can be solved by quadratic programming methods. In a numerical example, a linear programming problem with two constraints and two decision variables is provided to illustrate the solution procedure.

This paper presents a new interactive procedure for multiple objective linear programming problem (MOLP). In practical multiple objective linear programming applications, there is usually no need for the decision maker to consider solutions which are not efficient. Therefore, the interactive procedure presented here searches only among efficient solutions and terminates with a solution that is guaranteed to be efficient. It also can converge to nonextreme efficient final solutions rather than being restricted to only extreme efficient points of the feasible set. The procedure does not require sophisticated judgements or inputs from the decision maker. One of the most attractive features of the procedure however, is that the method allows the DM to examine the efficient faces it finds. As iteration goes, the DM can explore a wide variety of efficient faces rather than efficient faces confined to only certain subregion of the feasible set of problem MOLP since the efficient faces that the procedure finds need not be adjacent. This helps the DM explore the nature of the efficient set of problem MOLP and also helps the DM have confidence with a final solution. For these reasons, I feel that the procedure offer significant promise in solving multiple objective linear programs rapidly and in a satisfying manner to the DM.

Markov chain models can be used to predict the state of the system in the future. We extend the existing Markov chain models in two ways. For the stationary model, we propose a procedure that obtains the transition probabilities by appling the empirical Bayes method, in which the parameters of the prior distribution in the Bayes estimator are obtained on the collaternal micro data. For non-stationary model, we suggest a procedure that obtains a time-varying transition probabilities as a function of the exogenous variables. To illustrate the effectiveness of our extended models, the models are applied to the macro and micro time-series data generated from actual survey. Our stationary model yields reliable parameter values of the prior distribution. And our non-stationary model can predict the variable transition probabilities effectively.

A production control information system developed for multi-product, small-lot-sized production is presented. The system is composed of interrelated modules for production planning, shop floor control, and inventory/material management. The architecture of the system, functions of each module, and information processing procedures of each function are discussed.

This paper involves a study of developing the production scheduling system in a general job shop type mechanical factory. We consider realistic situations in the job-shop environments, such as alternative machines for operation, the new kinds of processes, the machining center with the plural pallet, the operational situation of each machine during the scheduling period, occurings of urgent orders and machine breakdowns. We also propose the methodology of re-schedule. It is very fast and acceptable for real time production control system. These all functions are implemented on IBM PC and program source is written in PASCAL language.

Strategic decisions related to the design of a physical distribution system can be classified into three basic components : facility location, transportation, inventory decisions. In this research the interdependence of those decisions are expressed in a mathematical model such that the total relevant cost of the system is minimized. We suggested a heuristic technique for solving the model. In broad terms, our solution technique combines a heuristic method for determining which candidate DCs to open and an exact method for minimizing costs given a set of open DCs. And we also developed a decision supporting package for the design of a physical distribution system.

Since the manufacturing machines containing information processing capacity by development of ME technology are developed and distributed from the advanced nations, manufacturing automation with manufacturing method which keeps flexibility and productivity is supplied broadly. An introduction of manufacturing automation technology is necessary to solve difficult domestic industry environment due to international competitiveness weakness of products. The aim of this is to search for the successful factors of the manufacturing business which uses too much technology of manufacturing automation and to observe the difference of the successful factors which influence to introduction performance according to the introduction type of automation technology and the strategic type through the empirical analysis.

The most important factors for a product to survive in the market are cost and quality. In recent years, quality proceeds to cost. There are many techniques of use to improve the quality of a product. One of the techniques is applying statistical methods (especially Taguchi method) to real operational conditions for a continuous manufacturing process in P company. There are 91 factors to control in the process. So, we predetermined 7 main effect factors and 6 interactive effect factors by statistical methods and advices of engineers. With these 13 factors, we determined the optimal level of operations for the process.

Traditional Manufacturing method is push system by plan made in advance and Japanese manufacturing method represented by JUST-IN-TIME is pull system which respond's to the demand flexibly. Both have their pros and cons. In general, it is well understood that push system is faster than pull system in the sense of manufacturing speed. However, pull system such as JIT excelles dramatically in the sense of work in process. Therefore, this paper is trying to put together to get alternative which has the advantage of both system. The objective of the paper is to enhance the effect of built-in manufacturing system without paying extra cost by way of introducing the alternative of the pull-push manufacturing strategic operational method.

Human Resource Management (HRM) performs numerous activities in organizations including employee recruitment, selection, placement, job analysis, training and development, and labor relations. POSCO (Pohang Steel Company) has concerned with employee management related to job placement and analysis among these activities because of the problems of over-complexity of placement precedures for the variety of recruits, the frequency of selection, a large amount of job descriptions / specifications, and their changes. This study, as a phase of developing the entire HRM systems in the organization, briefly summarizes the preliminary information related and describes an implementation of expert system as a means for effective job placement based on the principle of right-person-in-right-place with identifying aptitudes and personalities of employees. Thus, a new approach for developing a job description/specification using a formal specification language like Z is also proposed. The result of this study will cultivate the performance of personnel, prevent conflicts between labor and management, promote overall productivity of organization, as well as helpfully verify job analysis.

Based upon previous research, factors affecting office productivity with the Accounting Information Systems(AIS) were suggested, and the relationships between the factors and the office productivity with the AIS were hypothesized. The empirical results suggested that there are significant positive relationships between the factors such as the user participation, level of AIS utilization, internal AIS development and AIS technical sophistication and the office productivity with the AIS. According to the results, the office productivity increasing strategy with the AIS were proposed.

The purpose of this study is to deal with a forecast of probable failures facing up to the existing Korean universities and colleges in the early 21st century and with how each institution should cope with the situation before the failures actually take place. The methods used in this research are Scenario analysis, Factor and Cluster analyses in order to find out major factors having influence upon the operation and management of these universities and colleges. It's turned out that every institution is different from others and in fact unique in its make-up and so each will have different ways to deal with the impending failures and the crisis management problems strategically.