Industrial Management Studies

Abstract In this paper, we investigate a decentralized manufacturer-distributer supply chain. In addition to global advertisement, the manufacturer participates in the local advertising expenditures of distributer. Bi-level programming approach is applied to model the relationship between the manufacturer and retailer under two power scenarios of stackelberg game framework and the optimal policies in pricing, advertising, inventory management and logistics are identified. Two hierarchical genetic algorithms are proposed to solve the bi-level programming models. Based on collected data from Iranian automotive spare parts aftermarket, several numerical experiments are carried out to evaluate the validity of proposed models as well as the efficiency and effectiveness of solution procedures.

Abstract In a complex and volatile environment of the supply chain, any attempt to reduce the risks may increase or decrease other risks; thus, achieving an overall picture of the risks of supply chain and relationships between them are necessary and will lead to more effective and comprehensive strategy to response to risks. The purpose of this paper is identifying and extracting the potential risks of supply chain using interpretive structural modeling (ISM) approach. In order to do that, first an in-depth litreture review has done and Delphi method with content validity has used, and then, the ISM model, representing the structure of risks relationship has extract. The results show that the external environment supply chain risks (natural risks, political/social, policy and macroeconomic), at a low levels of the model, have the most impact on other risks and are as a emerging and or increasing factor for industrial environment (market and product competition; market inputs, communications and collaboration) and organizational environment risks (operational, financial, strategic, commitment and organizational culture and employee).

Abstract In this research, a multi-objective mixed integer programming model is presented to design a healthcare network with risk pooling effect. Since the model parameters have also uncertainty, for closing the model to reality, using robust optimization approach, the model is also extended in a state of uncertainty. Objective functions that have been used, include minimization of transportation costs, costs related to sterilization, as well as the movement of resources. We are also looking for maximizing the minimum level of service provision of healthcare centers to customers. Also, for solving the proposed model, we utilized a multi-objective fuzzy method which is developed in recent years. Moreover, several numerical examples are brought up to show the accuracy and validity of the model. The results obtained from this analysis, showed the accuracy of behavior of the model and the proposed approach in different modes. Computational results show that the robust model provides more high-quality solutions, in a way that it has far less standard deviation compared to deterministic model

Abstract The purpose of this study is investigating the effect of supply chain drivers on Qazvin manufacturing companies’ supply chain integration and company performance. The organizational culture has been used as a moderating factor in this relation. The study has 6 hypotheses in which data are gathered with questionnaire form 79 supply chain managers, as required sample, using structural equation model with the partial least square analyzed. The findings revealed that internal drivers have positive impact on supply chain integration. Also none of the dimensions of external drivers have positive impact on integration. As the results show, organizational culture mediates the relation between external drivers and supply chain integration, but does not mediate the relation between internal drivers and integration. Eventually, supply chain integration has a positive and significant impact on company financial and operational performance. The results of this study provide a comprehensive understanding to supply chain managers and lead them to identify effective factors on supply chain integration and improving company performance

Abstract Reliability optimization and mean time to failure are those of the areas of interest for engineers and designers of systems and the use of redundancy components is one of the most common approaches in this field. The purpose of the optimization problem, finding the optimum number of redundancy components that must be satisfied the objectives of reliability engineering in the system. But usually the reliability improves results in increased costs and changes in parameters such as volume and weight of the system; therefore, it is necessary to establish a balance between resources. In previous researches, redundancy allocation problem is studied with non-repairable components or failure rate with exponential distribution; but in this study, repairable components and rates of failure and repair a non-exponential distribution assumed. Thus the purpose of this paper is solving reliability redundancy allocation problem with the goals of increasing the mean time to failure, reduce costs and reduce the variance of the shelf life of the system, while taking into account constraints such as volume and weight of the system. To this end, the research effort will be using mathematical and statistical techniques such as multi criteria decision making models, design of experiments, simulations, and computer software associated with them, provide a new approach for solving reliability redundancy allocation problem in series-parallel systems with repairable components

Abstract Course timetabling is an important branch of the general scheduling problem. The course timetabling problem as a step in the course planning process in universities is one of the challenges faced by managers in the field of education. The problem is defined as assigning university courses to specific periods throughout a week for a given semester while satisfying specific constraints. In this study, we present two novel binary integer linear programming models for the university timetabling problem. Using a GAMS IP Solver, several experiments through each model are solved and the results (the number of the decision variables and solution time) are compared and analyzed. The computational comparison indicates that the second model can be used for modeling large-scaled problems and has less computational and size complexity. Therefore, the second model is applied to optimal scheduling the courses planned for the faculty of administrative science and economics (ASE) at Isfahan University for one semester and the results consist of table of courses planned for teachers, students groups, rooms and workdays are presented

Abstract Data Envelopment Analysis and Balanced Scorecard, are two common tools that have been used by many researchers for performance evaluation. But none of them investigate effectiveness of BSC indicators in efficiency evaluation. Due to complexity of mission and evaluation criteria for operating organizations in media industry, they want to know suitable indicators for effectiveness evaluation, also the role and importance of these indicators in organization efficiency. With responding to these questions, organizations can allocating resources and take decisions according to the importance of determined criteria. In this paper we purpose a novel and hybrid model of DEA and cooperative game theory to rank the effectiveness of BSC indicators in efficiency evaluation for iran media industry. Results show that (profitability ratio, size of audience, human resource satisfaction rate, accuracy in production, velocity of propagation and satisfied audience percentage) are respectively most important indicators. Therefore, with considering importance of criteria and resources constraints managers can take better decisions