نشریه بین المللی مهندسی صنایع و مدیریت تولید
سال بیست و دوم شماره 1 (بهار 1390)

The selection of proper bridge sites across a river depends on many factors such as economic, transportation and geomorphology. In this paper, the best sites for bridge building are identified in a case study by using analytical hierarchy process (AHP) and fuzzy logic in GIS environment. First, the river is divided into a number of segments based on the similar characteristics, each of which can be considered as an option for building the bridge. Then, main criteria of site selection are introduced and based on them; different layers of GIS are defined. The options failing to provide the minimum technical requirements for bridge building are removed. Remaining options are assigned weights with respect to each of three criteria. Pair-wise comparison is also performed among the criteria with respect to the opinions of three experts. Fuzzy logic is used to consider the uncertainty of pair-wise comparisons. Finally, the best sites are ranked based on fuzzy AHP method. Furthermore, as an old bridge is available at the river reach, two scenario including existence and nonexistence of the old bridge is also investigated.

In this paper, Multi-objective Flexible dynamic Job shop scheduling with maintenance constraints is investigated. In the recent researches the single objective models were assessed. Whereas in competitive conditions, decision makers encountered with simultaneous multi-objective problems that could be conflict with each other. In this research, the objectives are makespan, mean flow time and mean tardiness. These objectives are adaptable to the concept of just-in-time and supply chain management. In real world, machines may be unavailable for various reasons, such as maintenance. In this paper deterministic machine availability as a non-fixed availability is studied. Therefore a mathematical model and improved genetic algorithm with dynamic control parameters that changed through the algorithm is proposed to reducing the probability of early convergence and local optimum. Moreover a heuristic algorithm is proposed to solve maintenance sub-problem. Computational experiments for the three flexibility levels show that the best result of proposed algorithm without maintenance have 3.9%, 4.9% and 4.55% improvement and mean results have 4.9%, 5.33% and 4.6% improvement compared with existing methods. And with considering one, two and three maintenance, the mean of objective function have increased 4.68%, 9.48% and 11.75%. The results show the superiority of the proposed algorithm.

Ranking of a project's risks is considered an essential part of risk management process, especially when the number of risk factors increases. In the present study, a comprehensive structure of main risks existing in tunneling projects was initially prepared composed of 17 major levels and 196 sub-level, and these risks were subsequently ranked in tunneling project of Seymareh dam in South-West of Iran. To this end, group decision making method and weighted average were used for collection and aggregation of expert's judgment, respectively. In addition, linear assignment technique as one of decision making methods was employed in order to determine ranking of risks. Criteria for ranking were classified in two groups, namely primary and secondary classes. The primary index has been determined based upon probability and impact of risks on project goals (including: time, cost, quality and efficiency) with different weights. The second group of criteria included socio- economic impacts, environmental effects, risk proximity, risk exposure, relative uncertainty level and risk manageability. Taking advantage of linear assignment method, risks are better evaluated considering different criteria, and they are therefore ranked more realistically. It was concluded that the economical factors and regularity condition are the project most and least critical risks, respectively.

Today, having information about performance in all aspects both financial and non financial is extremely important in managerial decision making. Different models for measuring performance have been recommended. One of these models is Balanced Scorecard. Balanced Scorecard focuses on four perspectives: growth and learning، internal processes، customers and financial. Through the use of Balanced Scorecard، organizations can implement strategies in various directions and manage them well. Therefore، it is necessary to present and explain these strategies as through and in such a way that every member of organization is able to perceive them. This can be accomplished through the use of strategy maps. Various researches regarding Balanced Scorecard has been done. However serious attention hasnt been given to the relationship between cause and effect and the strategy map. In this article، we will be discussing a method using the DEMATEL technique to determine the relationship between cause and effect and the strategy map. Finally، the results of the implementation of the recommended model at a heavy equipment manufacturing plant will be presented.

The application of statistical process control methods to health care is facing an expansion in the recent days. In some statistical process control applications, quality of a process or product is characterized by a relationship between two or more variables which is referred to as a "profile". Profile monitoring method plays a very important part in statistical control process. Unfortunately eventhough it proved to be a successful application in some industrial cases it was not used in medical field so far. In this paper, profile monitoring, in phase I and II, is performed on Pulmonary Function Test for a patient. A profile that can be represented as a polynomial regression is used here. Among the existing methods in monitoring of polynomial profiles, F-approach and orthogonal polynomial method are considered for phase I and II respectively. This real case illustrates profile monitoring as an appropriate and effective method in improving health care.

Disaster relief logistics is one of the major activities in disaster management. The significance of accounting for uncertainty in such context stimulates an interest to develop appropriate decision making tools to cope with uncertain and imprecise parameters in relief logistics system design problems. This paper proposes a multi-objective possibilistic non-linear programming model (MOPNLP) to deal with such issues. Our multi-objective model contains: (i) the minimization of the sum of setup cost, transportation costs and shortage costs of commodity in affected area; (ii) the maximization customer satisfaction. The model includes the imprecise nature of some critical parameters such as demands for various types of relief commodities, cost coefficients and capacity levels. To solve the proposed model, a two-phase interactive fuzzy solution approach is developed. Numerical experiments demonstrate the significance and applicability of the developed possibilistic model as well as the usefulness of the proposed solution approach for actual decision making problem.

Success of manufacturing and service companies requires specific vision and mission statement, c orrect formulation of strategies and objectives, prioritization and execution of operational projects, evaluation and fair analysis of performance, and proper modification in the above five processes. One of the biggest challenges of executive managers today is the right formulation and deployment of strategies. Experience indicates that in most cases, strategies have been correctly formulated but poor execution in practice has led to failure. One of the major reasons for poor execution of projects is implementation of strategies which have low prioritization and consume a major part of resources. This paper based on SWOT, BSC, QFD, and EFQM presents an integrated framework for alleviating the above problem. This framework is used to formulate and implement strategies at the Islamic Republic of Iran postal company.

In recent years, Supplier evaluation and selection, an important element in supply chain management, has been gaining attention in both academic literature and industrial practice. The Mixed integer multi-objective Linear programming model (MIMOLP) presented in this paper aimed to evaluate and select the appropriate set of suppliers considering quantitative and qualitative criteria and in addition to selecting the first layer's suppliers which relate directly to the organization, analyses the characteristics of second-layers suppliers, and design a network to determine the flow rate of products and materials between buyers and best suppliers in both layers. Then allocate the optimum orders to each supplier. Another important feature of this model is considering quantity discounts for the first layer's suppliers and at the same time different kinds of products and raw material can be considered. Finally, the model is solved by using goal programming approach and numerical examples are presented to test the performance of proposed model.