JOURNAL OF INDUSTRIAL MANAGEMENT STUDIES
Year:2019 | Volume:17 | Issue:52 |Papers Count:10

Nowadays the process performance is a key success factor in the competitive environment of banking industry. Various approaches have been proposed to identify and improve processes. Process mining is a new process management approach which is supposed to discover and improve the actual process model based on information technology. Despite of the theoretical development, authors have paid less attention to process mining applicability. In this paper applicability of the Fuzzy Miner algorithm of process mining to semi-automatic processes is investigated. We used PM2 methodology with some changes at the first and the fifth step to discover a semi-automated process model. At the first step manual and system data is combined and the desired detail level is determined by process owners. Then the model is discovered by means of Fuzzy Miner algorithm through ProM tool. As the manual data could affect the discovered model adversely so besides conformance checking criteria a new expert based criteria is proposed to validate the model. The expert validation criteria is equal to 87. 2 percent for the discovered model of the selected process which means process mining could be applied to semi-automated processes successfully.

The companies for their growth and survival in competitive domains must develop new products; however, innovation required for this process is a risky and costly enterprise. Most of the scholars have considered the factors leading to success as static and they have not taken into account their dynamic nature. Since the relationships among the influential factors which can lead to the success of developing new products have various dynamics and feedbacks, tools for the identification of dynamics in such systems are among the most useful tools which can be used for investigative purposes in this domain. In the present study, which aimed at identifying and analyzing the dynamics of factors affecting the success of new product development, the key variables for the development of new products were identified based on the theoretical backgrounds and the ideas of experts in the industry and then the causal relationships among them were drawn. Subsequently, the mathematical relationships among these variables were determined based on the existing relationships among them in the literature and as a practical step the intended system was simulated in Nooshin Azar Food Company in the time span of 1384 to 1404. For improving the performance of the companies, policies like increased management support, more investment in research and development and improvement of product development planning were suggested and the results which can be derived by applying these scenarios were simulated as well.

The control and planning of operating rooms have became more and more important for hospital managers. Nowadays, the operating rooms, as key resources, often lead to a great time waste. So, appropriate scheduling of operations in order to increase the efficiency of the operating rooms, are significant research topics in medical care. In this study, a new linear programming model has been developed for the assignment of patients to the operating rooms. Since the duration of surgical procedure is a stochastic parameter, in this paper a two-stage stochastic programming model has been presented in addition the deterministic model. These presented models simultaneously investigate the scheduling of surgeries and allocating them to the surgery rooms. The aim of this study is to minimize the cost of assigning patients to unspecialized rooms and reduce the cost of doctors’ idle time per working shifts by taking into account the constraints. The suggested models were applied for the surgery department of Ghaem hospital of Mashhad and solved by ILOG CPLEX 12. 6. 1 Microsoft Visual Studio environment. The results show that the deterministic proposed model increases the average efficiency of hospital to 38. 275% and the stochastic model increases the average efficiency to 85. 32%.

One of the most important problems of logistic networks is designing and analyzing of the distribution network. The design of distribution systems raises hard combinatorial optimization problems. In recent years, two main problems in the design of distribution networks that are location of distribution centres and routing of distributors are considered together and created the location-routing problem. The location-routing problem (LRP), integrates the two kinds of decisions. The classical LRP, consists in opening a subset of depots, assigning customers to them and determining vehicle routes, to minimize total cost of the problem. In this paper, a dynamic capacitated location-routing problem is considered that there are a number of potential depot locations and customers with specific demand and locations, and some vehicles with a certain capacity. Decisions concerning facility locations are permitted to be made only in the first time period of the planning horizon but, the routing decisions may be changed in each time period. In this study, customer demands depend on the products offering prices. The corresponding model and presented results related to the implementation of the model by different solution methods have been analysed by different methods. A hybrid heuristic algorithm based on particle swarm optimization is proposed to solve the problem. To evaluate the performance of the proposed algorithm, the proposed algorithm results are compared with exact algorithm optimal value and lower bounds. The comparison between hybrid proposed algorithm and exact solutions are performed and computational experiments show the effectiveness of the proposed algorithm.

Value engineering is one of the tools to create and improvement value while reduces unnecessary costs and keeps the original function, leads to increased efficiency. Today this technique used to reduce the cost in industries that are facing high costs such as the electricity industry. The evidence and expert’ s opinion implying that many factors causing costs in the industry is related to the supply chain the low efficiency in the supply chain, resulting in increased costs. So to increase performance and reduce costs, the research was conducted aimed to identify and prioritize solutions reduce costs in the supply chain for cables and accessories combined cycle power plant Sirjan (Gol Gohar), who has a major role in the country's electricity supply. The final solutions for cost reduction after holding several meetings with experts of the project value engineering team were identified. Then these solutions were evaluated with criteria extracted of the research literature and opinions of experts of the project value engineering team were moderated and finalized. The final criteria and each of the sub-criteria were weighted by SWARA. Then final weight was calculated for each of the sub-criteria. In order to prioritize final solutions we used ARAS-G. After prioritizing solutions, solution the twelfth (reducing the time of order up to purchase and deliver through the reform procedures purchase), as the best solution was identified to reduce costs and thus increase performance supply chain target.

The increasing concern about the deteriorating effects of supply chains related activities on the environment has led to the growing attention to develop green closed-loop supply chains in order to minimize greenhouse gases emission. This paper presents a green closed-loop supply chain model developed under the demand uncertainty aiming at minimizing total cost and total CO2 emission across the supply chain, and maximizing the product’ s market share in the presence of a competitor. In this regards, an agent-based market model is developed to estimate the demand’ s parameter function then a hybrid simulation model which integrates agent-based and discrete event simulation modelling approaches is designed to simulate the closed-loop supply chain which is the novelty of this paper. Then, scenarios are created using Taguchi design of experiments (DOE) method, and are executed with the market model and the supply chain model to capture total cost, total CO2 and market share. A decision matrix is configured using scenarios and recorded results for three mentioned criteria and ELECTRE and SAW methods are used to rank scenarios and select the best one. The other contribution of this research is its comprehensiveness in considering variables related to three categories of inventory replenishment policy, marketing mix (price and advertisement) and transportation. An automotive industry case is provided to demonstrate the capabilities of the model and its applicability and effectiveness in resolving real-world problems.

There is a serious competition between Allameh Tabataba'i, shahid Beheshti, and Tehran Universities to attract the best students. In other side, students have considered several indicators to choose university for higher education. The aim of this research is to determine management faculties’ competitive position in these Universities and also to find an answer to this question: what is the position of Allameh Tabataba'i University postgraduate students compared to two other universities based on variables such as: rank of entrance examination, number of acceptance, average of undergraduate scores, type of undergraduate university, relationship between educational field in BS and MA, and students age. This practical research uses descriptive study and has comparative approach. The data was collected from three management faculty for 2009 to 2014. The findings indicate that Allameh Tabataba'i University has accepted MA students in management more than two other universities and its MA students have lower average of entrance examination rank. There were no main distances on average of undergraduate scores and MA students’ age between these universities. There were similar situations about the other variables.

Today, intense competition in global markets has forced companies to design and manage of supply chains in a better way. Since the role of three factors: location, routing and inventory is important to continue the life of a supply chain so, integration of these three elements will create an efficient and effective supply chain. In this study, we investigate the problem of supply chain network design that including routing and inventory problem consist of flow allocation, vehicle routing between facilities, locating distribution centers and also consider the maximum coverage for respond to customer demand. Proposed mathematical model is a nonlinear mixed integer programming model for location-routing-inventory problem in the four-echelon supply chain by considering the multiple conflicting goals of total cost, travel time and maximum coverage. In order to solve the proposed model, three meta-heuristic algorithms (MOPSO, MSGA_II and NRGA) has been used. The accuracy of mathematical model and proposed algorithms are evaluated through numerical examples

Supply chain (SC) coordination is one of the major issues which has been considered in the investigations of supply chains. In this study, a two-echelon supply chain with one retailer and one supplier is considered. Demand is stochastic and has a normal distribution and lead time is assumed deterministic. The retailer uses a periodic review inventory system for his replenishment decisions and faces partial shortages. Review period and order-up-to-level are decision variables of the retailer. First, the optimized values of the variables in both decentralized and centralized decision-making structures are obtained. Although Centralized decision making increases the whole SC’ s profitability, it reduces the profitability of the retailer in comparison with the decentralized model; In order to make centralized decisions and to encourage the retailer to change his decisions, a coordination model is proposed. Quantity discount contract is used as an incentive scheme in the coordinated model. For calculating the exact value of the discount factor in this contract, the both member’ s profit is considered. Furthermore, to fairly share the extra profit achieved by the coordinated model, a profit-sharing strategy, based on the bargaining power of the members, is proposed. A set of numerical experiments and sensitivity analysis, which is performed with respect to several key parameters of the study, reveal that, from economic viewpoint, the proposed coordination model for the supplier-distributor channel, can increase the channel profit up to its optimal profit level and guarantee the improvement of channel members’ profit in comparison with their profit under the decentralized model. From inventory management viewpoint, the proposed discount contract reduces the distributor’ s inventory shortage risk. Moreover, results of evaluating the proposed model under high levels of demand uncertainty shows that the proposed model is capable of coordinating the SC under various conditions such as demand frequencies and high quantities of standard deviation of the demand.

The selection of project portfolio is the main problem in project-based organizations. In project selection, optimized decision to maximizing utilization of limited resources and achieving organizational goals by considering restrictions are important. Therefore, to facilitate project portfolio selection in project-based organizations, an efficient model is proposed that is able to consider limitations, goals, and priorities of the organization in selecting the optimal combination of projects. The proposed model is a hybrid and flexible one which, including four main steps. First, with initial screening, to save time and money by using non-compensatory method, some of the poor candidate options are deleted. Then, due to multi-criteria nature of the problem, qualitative and quantitative criteria, and uncertainty of data in real world, the projects are ranked using fuzzy analytic hierarchy processes and uncertain judgments of decision-makers. To generate project baskets, integer linear programming (ILP), backpack model, is employed modifying the coefficients of the objective function of each project to preserve multi-criteria rating of projects, and then evaluate and rank the baskets. To validate the proposed model, we have carried out selection of project portfolio in the oil refining industry.