فصلنامه مطالعات مدیریت صنعتی
پیاپی 18 (پاییز 1389)

Maximal Covering Location Problem (MCLP) aims at maximizing a population of customers which are located within a specified range of time or distance from some new servers which should be located. A number of extensions have been proposed for this problem, one of which is considering queuing constraints in the model. For an example, location of a limited number of servers in such a way as to maximize the covering considering the constraint regarding to the queue length. In this paper, we extend the proposed model by Correa and Lorena [3] which maximizes the covering. We consider a more objective function in such a way as to minimize the total distance between the servers and demand points. A genetic algorithm based heuristic is proposed to solve the model and results are compared with that of given by CPLEX as a standard solver to estimate the performance of the given algorithm.

Some problems of real world, must be determin and analyze input variable's effect on response variable. One of the applicable techniques which are used for modeling and solving such problems is response surface methodology (RSM). In this paper the effect of five controllable input factors: raw materials, electromotor speed, stove temperature, furnace temperature and air pressure on the determined response surface level i.e. theresistance of glass bottle is checked by design of experiment (DOE). After the execution of experiments and the recognition of effective factors, according to the application of RSM, the relationship between variables of effective input factors and the response surface variable is determined by nonlinear regression model. Then, the optimal value of each variable in nonlinear model is obtained by goal programming method.

Globalization and competitiveness have undergone earthquakes, tremors and aftershocks on global manufacturing environment, that have forced manufacturing organizations to restructure and change way of doing their business. Furthermore, manufacturingorganizations have realized that agility is essential to survive and competition. But, the ability to build agile manufacturing componies has developed less than anticipated. Because, manufacturing organization managers faced with this problem that how much agility an organization currently posses, determining how much is needed. Inthis article, an hierarchical model based on fuzzy weighted average technique in order to support manager's decisions for building manufacturing agile is Presented. This model can capture the vague and uncertainty of agility indicators, and the expert's knowledge andjudgment. The model was performed in Khozestan's Steel industry.

Today, different types of proactive organizations can be classified in service and industrial organization sectors. The first type of organizations are located in developing countries and have had broodbased activities. The second type organizations operate developedcountries and are more important in terms of value creation and economic operations. What is apparent in literature review and conceptual model and theory is that, the respective issues are more relevant to industrial organizations which have measurable tangible activity and performance. Therefore, service organizations are toutilize knowledge in accordance with its environment and structure. In this research, quality findings enable organizational managers to improve and present better service quality and operations. Regarding this issue, literature on organizational excellence modelsare reviewed. After identifying scientific dimensions of subject matter, with respect to expert knowledge and executive managers who are involved in service, and industrial organizations, an excellence model is analyzed and introduced. All data collected and evaluated regarding: Deming, Baldrige EFQM (the European Foundation for Quality Management)and CAF (Common assessment Framework), theoretical Excellence model evaluated thoroughly by all organizational managers working repeatedly and continuously in strategic, technical and scientific committees throughout IDCO organizations. Thereby final conceptual excellence model approved and authorized by organization for implementation.

Traveling salesman problem (TSP) is one of the most well known combinational optimization problems which recently has been a suitable base to validate different heuristic and Meta heuristic algorithms. Multiple application of this problem in both theoretical and operational field is remarkable to researches. Mate heuristicOptimization algorithm by ant colony is a kind of successful methods which has been used to solve discrete combinational optimization problems recent years. An algorithm based on ant colony optimization is presented in this paper to solve fuzzy traveling salesman problem. Presented algorithm has been programmed and run at C++environment and results of each run were compared with coded results of Branch and Bound algorithm by Lingo 8.0. Suggested algorithm has resulted successfully in small scale and in the case of large scale has resulted to feasible solution at short time.

In this paper, a single-product three-echelon supply chain with the loops of manufactures-distributors-customers has been considered where the customers demand, the percent of rejected product from customers and the shipping time of product from distributors to customers are considered as fuzzy variables. The main approach in this paper is simultaneously consider ation of suppliers and distributors selection problems and to determine effective customers in the system under uncertainty. The purpose of thispaper is to present a model which aggregates conflicting objectives between loops of this chain, increases the number of uncertainty parameters of the model as well. Hence, the objectives of the proposed model are: to maximize quality of products, to minimize total cost, to minimize product shipping time from distributors to customers and to maximize obtained earning from product selling to customers. Also in the proposed model, some constraints are considered such as the orders shortage, the production capacity anddemand of customers. The proposed model will be illustrated by a numerical example for the three-echelon supply chain problem and will be analyzed based on α-cut levels.

At the present time, suitable and on time response to customers need’s is the most important factor for success, and many organizations focus on quality according to ISO standards. This quantitative – descriptive study, was conducted related to the barriers and problems of ISO implementation in manufacturing companies, reviewing the critics andsupports toward the ISO all overthe world and then investigates the reason for mal implementation in manufacturing companies of the country.Research data were gathered through a19 item questionnaire regarding the implementation of ISO standards (ISO 9000:2000) in lickerts format.The society of study includes all companies intending to achieve ISO 9000:2000 supervised by the ministry of industry in Tehran province. It was requested that, three middle level managers answer the questions. After two months, 54 companies completed the questionnaires.Results showed that the implementation of ISO management system in every organization’s needs are foundation procedure and also top level managers and authorities should accept such process in their organizational management practice. Such evidence was not observed in this study and in contrast there was a little trend in this field whichdid not motivate the managers to provide the needed infrastructure for documentation, data transfer and contribution with other management levels. It seems that top level managers of Iranian Industrial companies do not pay significant attention to such important problem and it will be followed by many negative consequences for localmanufaturing centers in their future competition in the world economy.