فصلنامه مطالعات مدیریت صنعتی
پیاپی 45 (تابستان 1396)

In this paper, the problem of job scheduling and preventive maintenance activities is investigated simultaneously in an unrelated parallel machine’s environment with machine deterioration. Due to the existence of deterioration phenomenon and its effect on the job scheduling, the aim of this paper is to find the ideal time, the optimum number of maintenance activities and the sequence of the jobs, for minimizing the sum of job's completion times. Preventive maintenance activities may be needed because of tool wears or machine deterioration in a job scheduling horizon. Here, two different deterioration time function and tool wear are studied, in which the machines are reverted to the original condition after any preventive maintenance activity. The duration of each activity is considered as a function of its starting time and its position on the sequence of job scheduling. A mathematical model is proposed and due to its complexity, a simulated annealing Mehta-heuristic algorithm is used for solving the model. Finally, numerical examples are given and sensitivity analysis with various parameters is applied to evaluate the performance of the proposed method.

Nowadays, customers are the most important sources of income for financial institutions and banks. According to the privatization process in the country and financial restrictions of banks, it is necessary to maintain and attract more profitable customers. Though, one of the most important methods to identify profitable customers is the concept of customer lifetime value (CLV) but it is more important to estimate customers’ future conditions because a bank`s future profitability highly depends on the customers situation.
In this research, the issues about CLV, the necessity and different classification methods are presented. Then, considering weighting variables using Recency, Frequency, and Monetary (RFM) model, AHP technique, and experts opinion, customers are classified. Using Markov chain and probability matrix, the displacement of customers in different groups and their future status are predicted.
One of the major outcomes of this research is the calculation of profitability matrix to predict customers’ displacement in different groups. The probability matrix can also show the reluctance of large number of customers to move to the specified groups (the highest percentage of customers in the main diameter of the probability matrix). In this research, we observed that account balance (M) has the greatest impact on customers grouping and that the number of transactions (F) and recency variable (R) are ranked as the second and third impact factors. Also, the determination coefficient (C) is another result of the research. Finally, the presented research used financial information and proposed a mathematical model (Markov chain) to calculate the probability of customers’ displacement (switching from one group to another). The proposed model can be helpful to facilitate customer relationship management process in the banking system.

Due to fierce competition and customer demand, manufacturers have started selling products with different warranty policies and pro-rata warranty is one of the most widely used warranty policy. In this paper we propose a warranty model for pro-rata, fixed period warranty policy with risk averse manufacturer that determines optimal warranty price under inflationary condition.
This model has been proposed for products with time dependent failure intensity with Non homogeneous Poisson’s process for failure intensity function, and concave utility function. Using the exponential utility function, the decision model is developed to maximize the manufacturer’s certainty profit equivalent. Risk preference model is developed to find the optimal warranty price through the use of the manufacturer’s utility function for profit. Finally, the sensitivity of the warranty price models is analyzed using numerical examples with respect to such factors as (1) the manufacturer's risk preferences, (2) product failure rate parameters, (3) warranty period length, and (4) inflation and discount rate.

Cross-docking is one of the lean logistics tools that is used for uniting the shipments during the loops replacement. Cross-docking is the process of product movement form distribution centers without storage function. Vehicle routing problem in Cross-Dock external environment has much influence on cross-dock costs. This paper provides a model for minimizing total distance traveled by vehicles in the external environment of a cross-dock. In this paper, Vehicles routes was modeled with capacitated vehicle routing problem (CVRP) and genetic algorithm (GA) was used to solve the model. To validate responses obtained by GA, simulated annealing (SA) was used. Also, to evaluate the efficacy of two algorithms (SA & GA) in different CVRP problems in cross-dock, 10 problems with different dimensions are evaluated. The results show that in problems with smaller size GA is more efficient, whereas in large size problems SA is more efficient.

Increasing the complexity of decision-making problems leads to utilize a group of experts instead of one expert for evaluating the contractor selection problem. This paper proposes a hesitant fuzzy preference selection index method based on risk preferences of experts. The hesitant fuzzy set is used to cope with the uncertainty in vague/hesitant situations. Also, the compromise solution is proposed to compute the weight of each expert. Moreover, the proposed approach considers the quantitative and qualitative criteria and also assists the experts to reduce margin of errors by assigning some membership degrees for each contractor versus each criterion under a set. In addition, the expert's judgments are aggregated in the last step of proposed approach in the group decision process to avoid the data loss. In the presented approach, selecting the best contractor is based on closest to positive ideal and farthest from negative ideal, simultaneously. Finally, the proposed method is applied to a case in construction industry for selecting the suitable contractor, in which the obtained results are compared with two decision methods from the recent literature to indicate the efficiency and validity of the proposed method.

Nowadays, most of developed and developing countries, because of both limited resources and growing competitive markets, looking for to diagnose the causes of projects delay and are trying to develop solutions for decreasing amount of delay in next projects. In this paper initially notions related to delay, project risk management, Failure Mode Effects and Analysis (FMEA) method have been reviewed and also construction projects of Kurdistan state organization of schools renovation have been examined. Then a framework based on Fuzzy FMEA and AHP model have been proposed in order to recognize the most important risks and determining the amount of effects of these risks on main objective of projects (i.e. time, cost and quality) and estimating their occurrence probabilities. Meanwhile along with calculating importance coefficient of factors, some ideas to prevent or decrease consequences of these factors have been recommended.

Delay is a common occurrence in the country's construction projects. Identifying delay factors in these projects and determining the influence of these factors is necessary to achieve the objectives of management. In this study, the effective delay factors on construction projects are identified by using previous studies, project documents and experts opinions. Since these factors affect on each other, the fuzzy cognitive map has drawn for effective factors and assessment factors or management objectives. Then, the effect of each factor on the assessment factors are evaluated by using hybrid learning algorithm and prioritization factors are done by using fuzzy data envelopment analysis. The results of the survey in West Azerbaijan province show that “supervision technical weaknesses for overcoming technical and executive workshop problems”, “inaccurate estimate of workload, required equipments and project time” and “the multiplicity of decision centers on the doing of projects” are the most important delay factors in construction projects.