INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING AND PRODUCTION MANAGEMENT (IJIE) (INTERNATIONAL JOURNAL OF ENGINEERING SCIENCE) (PERSIAN)
Year:2010 | Volume:21 | Issue:2|Papers Count:14

In the recent years, theory of constraints (TOC) has emerged as an effective management philosophy for solving product mix problem with the aim of profit maximization by considering the bottleneck. Furthermore, Fuzzy set theory has been used to model systems that are hard to define precisely and represents an attractive tool to aid research in production management when the dynamics of the production environment limit the specification of model objectives, constraints and the precise measurement of model parameters. In this research, an algorithm based TOC is proposed for product mix problem with bottleneck(s) and fuzzy processing time and fuzzy capacity. The efficiency of this algorithm compared with Fuzzy Linear Programming (FLP), TOC heuristic, Revised-TOC(RTOC), Hybrid Tabu-SA, genetic algorithm, and tabu search through three illustrative examples but in this comparison, we focused on FLP. The results have shown inefficiency of TOC in fuzzy state.

This paper presents a multi-objective cell formation problem considering alternative process routes and machine utilization. Three conflicting objectives, namely 1) minimizing the total cost consisting inter-cell movements, procurement, operation and maintenance; 2) maximizing the total machine utilization in the manufacturing system; 3) minimizing the deviation levels between the cell utilization (i.e., balancing the workload between cells) are considered. Since this problem is NP-hardness, a multi-objective scatter search (MOSS) method based on TOPSIS is designed in order to find locally Paretooptimal frontier. To demonstrate the efficiency of the proposed MOSS, a number of test problems are solved and the related results are compared with the well-known multi-objective genetic algorithm, called NSGA-II, based on some quality measures. The computational results indicate the superiority of the proposed MOSS compared to the foregoing NSGA-II.

In this paper, a robust multi-objective model to optimally control the lead time of a complex assembly system is introduced. The system is modeled as an open queue network, whose service stations represent manufacturing or assembly operations. It is assumed that the products arrive independently according to a Poisson process. In each service station, there is either one or infinite number of servers with exponentially distributed processing time. Each service station produces uncertain but limited number of scraps which are independent from the other service stations. The transport times between the service stations are independent random variables with generalized Erlang distribution. Addressing the data uncertainty, the problem is formulated as a robust multi-objective optimal control problem that involves three types of conflicting objective functions. The types of objective functions are the total operating costs of the system per period, the average lead time and the variance of the lead time. Finally, we use the goal attainment method to solve a discretetime approximation of the original problem to obtain the optimal service rates of the problem.

The aim of this paper, using a combination approach for fuzzy hierarchical analysis and balanced score card to assess the business climate in the industry in Iran. In the first part of the situation and favorable business environment in more reviews and Economic Intelligence Unit the results based on four aspects of balanced score card categories are analyzed. Indicators extracting fuzzy hierarchical analysis process has been weighted in proportion to their empowerment strategies for private sector survey design experts and 62 major strategies to identify and then select the most effective strategies to prioritize TOPSIS method used and finally 16 poll Grand strategy was selected. Appropriate strategies and operational solutions to the above interviews with experts and Library Studies to identify and extract the most effective solutions, expert persons development organizations affiliated to the Ministry of Industries and Mines of choice (a total of 30 organizations from every 5 persons) and questionnaire design those with the most important guidelines applicable to the study population and a total of 64 large-scale solution, was selected.

In the last 15 years, some methods have been proposed for forecasting based on fuzzy time series. One of the most important issues that affect the forecasting results in these models is the length of intervals. There are some studies on this issue but in most of them, length of intervals are predefined or even in some studies the interval’s length are the same. In this study we propose a model to determine effective intervals by using Simulated Annealing algorithm. And then we exercise this model on the FOREX currency market on some currency exchange rates (EUR/USD euro/US dollar, CAD/USD US Dollar/Canadian Dollar, GBP/USD British Pound/US Dollar, GBP/CHF British Pound/Swiss Franc) also we compare our model with other’s on forecasting Alabama University Enrollment.

The Vehicle Routing Problem (VRP) is one of the most important combinational optimization problems that has nowadays received much attention of researchers and scientists. In this problem, the objective is to minimize the cost traveled by several vehicles that start to move simultaneously from depot and come back to depot after visiting customers if at first each node is visited only once by one of the vehicles and at second each vehicle does not load more than its capacity during the route. This paper presents a hybrids meta-heuristic algorithm for solving the classical vehicle routing problem. At the first stage, a modified genetic algorithm for finding a suboptimal solution is applied in which a new crossover method for combination chromosomes is proposed. Then at the second stage, the 3-opt algorithm is used for finding better solutions. Extensive computational tests on standard instances from the literature confirm the effectiveness of the presented approach.

This article describes a knowledge management (KM) success model that is derived from observations generated through an empirical study of KM in an Iranian consultant company and KM success factors in the literature which is shown that company has a weak situation in each factor. So company needs a measurement model in order to assess knowledge management implementation processes in each step through the situation of CSFs and other important measurement indexes. The DeLone and McLean (1992, 2003) IS success model is used as a framework for the model, since it is found to fit the observed success criteria and provide an accepted theoretical basis for the proposed model.