فصلنامه مطالعات مدیریت صنعتی
پیاپی 29 (تابستان 1392)

A Resource Investment Problem is a project scheduling problem recently considered. In this issue, in contrast with other project scheduling, the project availability of needed resources level is considered decision variable and the goal is to find a schedule and resource requirement level. Researches regarding this field are related to optimizing an objective. In this paper, resource investment problem is studied for simultaneous optimization minimizing projectspan and project resource costs. Two multi-objective meta-heuristic algorithms, two process sub-population genetic algorithms and multi-population genetic algorithm are proposed to find solutions. According to evaluation criteria, the function of two algorithms is computationally compared and.

The development of Multiple Criteria Decision Making Techniques is to provide the possibility of using multiple criteria in decision making problems. Multi-criteria decision making problems primarily relate to choosing the best option among several available options and according to some indicators. One of the major issues in this regard is to determine the importance weights of decision criteria. Various methods such as Entropy, LINMAP and Saaty’s method have been presented for determining the weights of the indicators. In this paper, a non-linear model based on the logic of TOPSIS method is proposed to estimate the ideal weights. Simplicity, Reduction of received data from the decision makers in the evaluation process, and the possibility of considering his comments about the preference of indicators to each other can be cited as the advantages of this method.

In this paper, based on the background of cost-oriented assembly line balancing problems, a novel mathematical model for scheduling and balancing the assembly line is offered that with the combination of task sequence-dependent setup time, parallel stations and resource constraint, minimizes the operational and investment costs of assembly system. Due to the complexity of the problem, the equations have been proposed to reduce the number of variables of the model, and to achieve the optimal solution in reasonable time using exact algorithms. To clarify and explain the features of the model a numerical example have been used. Also the solutions obtained from model in several examples, have been analyzed using different indexes, and results indicative of appropriate performance of the model.

In this paper, we present a MCDM model for vendor selection of Telecommunications systems. Decision making in Telecommunications systems (Central) is more important because of their communicational role in organizations. Considering the multiple criteria in the vendor selection of telecommunications systems is a multi-criteria problem. Because these decisions usually are based on the intellectual judgments of managers, Fuzzy logic is used to improve decision making. Literature review and experts opinions used for determining the model indexes and then developed a Fuzzy TOPSIS model with combined weighs. Combined weights are result of integrating various methods such as intellectual judgment of managers, Fuzzy statistical average, modified weight and fuzzy weigh. In this model all numbers are Fuzzy and triangular type. A case study done in Qazvin Islamic Azad University to apply the developed model.

A major cause of supply chain deficiencies is the bullwhip effect. This phenomenon refers to demand variability increases as one move up the supply chain. Supply chain managers experience this variance amplification in both inventory levels and orders. Other side, dampening variability in orders may have a negative impact on customer service due to increase in inventory variance. The contribution of this paper is the estimation of the bullwhip effect and stock functions with using of response surface method under causes of the bullwhip effect in a three stage supply chains consisting of a single retailer, single wholesaler and single manufacturer with both centralized and un-centralized chains and show that with Considering the importance of the bullwhip effect reasons and interactions between them, the percent of optimal reasons and interactions between them and the level of desirability of bullwhip effect and net Stock will be illustrated by a model.

The main purpose of this practical survey is devoted to identify the obstacles of strategic plan implementation among energy sector's contractors and then, to present a classification of identified obstacles on the basis of their priorities. In order to achieve this purpose, 8 factors were chosen as the obstacles of strategic plans in energy sector following the literature review and experts comments, and then applied to 87 managers and senior experts of strategic planning in contracting firms by a questionnaire. The Fuzzy TOPSIS technique is assumed as a well-known Multiple-criteria Decision Making (MCDM) approach. Results showed that organizational structure was received the most priority as an obstacle in implementing strategic plan in contracting industry and operational planning, resource allocation, quality of strategy, communication, strategy executors, control and commitment got subsequent ranks. So, findings of this survey could improve the efficiency of contracting firm's managers to direct the process of strategy implementation and to overcome on identified obstacles.

As the most important institutions, Banks face different risks. As a matter of fact, risk is the results of the internal - external elements and the stakeholder’s expectations of the current and future status of the banks which are active in the country. Under a poor management some of this risks which forces called strategic risks may cause bankruptcy. One characteristic of mature banks is the development of a certain integrated processes of risk management. Due to the necessity of applying this approach in banking, we chose the Mellat Bank as a case study in this article. Our goal in this research was acquiring knowledge of banking experts to reveal and document strategic risks by use of Delphi methodology. This research is up to identify and rank the strategic risks of Mellat Bank and draws the strategic risk map.