Sharif Digital Repository

The redundancy allocation problem (RAP) is a useful method to enhance system reliability. In most works involving RAP, failure rates of the system components are assumed to follow either exponential or k-Erlang distributions. In real world problems however, many systems have components with increasing failure rates. This indicates that as time passes by, the failure rates of the system components increase in comparison to their initial failure rates. In this paper, the redundancy allocation problem of a series-parallel system with components having an increasing failure rate based on Weibull distribution is investigated. An optimization method via simulation is proposed for modeling and a... 

Diabetes mellitus is a medical condition examined by data miners for reasons such as significant health complications in affected people, the economic impact on healthcare networks, and so on. In order to find the main causes of this disease, researchers look into the patient's lifestyle, hereditary information, etc. The goal of data mining in this context is to find patterns that make early detection of the disease and proper treatment easier. Due to the high volume of data involved in therapeutic contexts and disease diagnosis, provision of the intended treatment method become almost impossible over a short period of time. This justifies the use of pre-processing techniques and data... 

The primary objective of this research is to obtain an accurate forecasting model for the US presidential election. To identify a reliable model, artificial neural networks (ANN) and support vector regression (SVR) models are compared based on some specified performance measures. Moreover, six independent variables such as GDP, unemployment rate, the president’s approval rate, and others are considered in a stepwise regression to identify significant variables. The president’s approval rate is identified as the most significant variable, based on which eight other variables are identified and considered in the model development. Preprocessing methods are applied to prepare the data for the... 

Supply chain management has gained much interest from researchers and practitioners in recent years. Proposing practical models that efficiently address different aspects of the supply chain is a difficult challenge. This research investigates an integrated production-distribution supply chain problem. The developed model incorporates parties with a specified number of processes to obtain raw materials from the suppliers in order to convert them to semi and final products. These products are then distributed through warehouses to end-distributors having uncertain demands. This uncertainty is captured as a dynamic stochastic data process during the planning horizon and is modeled into a... 

In this research, a maximal covering location problem (MCLP) with real-world constraints such as multiple types of facilities and vehicles with different setup costs is taken into account. An original mixed integer linear programming (MILP) model is constructed in order to find the optimal solution. Since the problem at hand is shown to be NP-hard, a constructive heuristic method and a meta-heuristic approach based on genetic algorithm (GA) are developed to solve the problem. To find the most effective solution technique, a set of problems of different sizes is randomly generated and solved by the proposed solution methods. Computational results demonstrate that the heuristic method is... 

This paper introduces a new hub-and-center transportation network problem for a new company competing against an operating company. The new company intends to locate p hubs and assign the center nodes to the located hubs in order to form origin–destination pairs. It desires not only to maximize the total captured flow in the market but also aims to minimize the total transportation cost. Three competition rules are established between the companies which must be abided. According to the competition rules, the new company can capture the full percentage of the traffic in each origin-destination pair if its transportation cost for each route is significantly less than of the competitor. If its... 

In recent years, much attention has been given to monitoring multistage processes in order to effectively improve the product reliability. To this end, the output of the process is investigated under special circumstances, and the values corresponding to reliability-related quality characteristic are measured. However, analyzing reliability data is quite complicated because of their unique features such as being censored and obeying nonnormal distributions. A more sophisticated picture arises when the observations of the process are autocorrelated in some cases, which makes the application of previous control procedures futile. In this paper, the accelerated failure time (AFT) regression... 

Monitoring the mortality associated with a surgical procedure leads to the proper decision making in a healthcare system. However, the surgical outcomes depend not only on the risk factors of each patient but also on other categorical influential covariates which cannot be easily measured. Ignoring the unmeasured covariates leads to the poor performance of monitoring procedures. To deal with this significant issue, a general Phase-I risk-adjusted cumulative sum control chart is proposed using a combination of accelerated failure time and frailty models to monitor surgical outcomes. Extensive simulation studies are conducted which reveal that the proposed frailty-based CUSUM chart outperforms... 

Monitoring the mortality associated with a surgical procedure leads to the proper decision making in a healthcare system. However, the surgical outcomes depend not only on the risk factors of each patient but also on other categorical influential covariates which cannot be easily measured. Ignoring the unmeasured covariates leads to the poor performance of monitoring procedures. To deal with this significant issue, a general Phase-I risk-adjusted cumulative sum control chart is proposed using a combination of accelerated failure time and frailty models to monitor surgical outcomes. Extensive simulation studies are conducted which reveal that the proposed frailty-based CUSUM chart outperforms... 

Using control charts to monitor healthcare systems has gained particular attention. In this paper, a risk-adjusted cumulative sum control chart is designed to monitor surgery outputs. Before undergoing surgery, the patients have some unique risk factors which influence the surgery outputs. Thus, risk-adjustment is carried out with the purpose of taking these risks into account using an accelerated failure time model. But the technical implementation of the chart requires determining the design parameters which should be selected in an optimal way putting the desired statistical and economic considerations into service. To this end, a multi-objective model, considering multiple assignable... 

Using control charts to monitor healthcare systems has gained particular attention. In this paper, a risk-adjusted cumulative sum control chart is designed to monitor surgery outputs. Before undergoing surgery, the patients have some unique risk factors which influence the surgery outputs. Thus, risk-adjustment is carried out with the purpose of taking these risks into account using an accelerated failure time model. But the technical implementation of the chart requires determining the design parameters which should be selected in an optimal way putting the desired statistical and economic considerations into service. To this end, a multi-objective model, considering multiple assignable... 

In this paper, a mathematical formulation is first derived for a homogenous fuzzy series–parallel redundancy allocation problem, where both the system and its subsystems can only take two states of complete perfect and complete failure. Identical redundant components are included in order to achieve desirable system reliability. The components of each subsystem characterized by their cost, weight, and reliability, are purchased from the market under all-unit discount and incremental quantity discount strategies. The goal is to find the optimum combination of the number of components for each subsystem that maximizes the system reliability under total fuzzy cost and weight constraints. An... 

The facility location problem and its related financial issues have a significant impact on the configuration of a supply chain structure (SCS). Although affording the setup cost of facilities requires a huge financial investment, a meticulous planning to recoup it has been neglected by an overwhelming majority of previous studies. To fill this gap, an economical investment plan of facilities is determined by striking a trade-off between the contribution of the stockholders’ capital and the loan arrangement. In the context of a multiperiod three-echelon SCS, the model also determines the optimum location of plants and the best supply and distribution patterns. The model maximizes the fill... 

In this paper, two control charts based on the generalized linear test (GLT) and contingency table are proposed for Phase-II monitoring of multivariate categorical processes. The performances of the proposed methods are compared with the exponentially weighted moving average-generalized likelihood ratio test (EWMA-GLRT) control chart proposed in the literature. The results show the better performance of the proposed control charts under moderate and large shifts. Moreover, a new scheme is proposed to identify the parameter responsible for an out-of-control signal. The performance of the proposed diagnosing procedure is evaluated through some simulation experiments. © 2017 Taylor & Francis... 

The rising disruptions of interdictors force supply chains’ designers to embody the protection decisions when locating the facilities. In the presence of variability in the intensity of disruptions, a risk measure is incorporated into the decision-making. The designer-interdictor bi-level problem, therefore, optimizes the joint location and protection decisions with respect to the conditional value-at-risk. This configuration has been absent from the literature. An accelerated modified Benders decomposition algorithm is developed and enhanced by being hybridized with a sample average approximation-based genetic algorithm. We examine how this new configuration influences the optimal solutions... 

In some statistical process control (SPC) applications, quality of a process or product is characterized by contingency table. Contingency tables describe the relation between two or more categorical quality characteristics. In this paper, two new control charts based on the WALD and Stuart score test statistics are designed for monitoring of contingency table-based processes in Phase-II. The performances of the proposed control charts are compared with the generalized linear test (GLT) control chart proposed in the literature. The results show the better performance of the proposed control charts under small and moderate shifts. Moreover, new schemes are proposed to diagnose which cell... 

Processes with multiple correlated categorical quality characteristics are called multivariate categorical processes. These processes are usually shown by contingency tables and are characterized by log-linear models. In this paper, two monitoring approaches including likelihood ratio test (LRT) and F test are developed to monitor multivariate categorical processes based on the contingency table in Phase I. In addition, a change point estimator for multivariate categorical processes is developed in Phase I. The performances of the two proposed approaches are evaluated in terms of probability of signal, while the performance of the proposed change point estimator is evaluated in terms of... 

This paper discusses the use of multi-response surface optimization (MRSO) to select the preferred solutions from among various non-dominated solutions (NDS). Since MSRO often involves conflicting responses, the decision-maker's (DM) preference information should be included in the model in order to choose the preferred solutions. In some approaches this information is added to the model after the problem is solved. In contrast, this paper proposes a three-stage method for solving the problem. In the first stage, a robust approach is used to construct a regression model. In the second phase, non-dominated solutions are generated by the ε-constraint approach. The robust solutions obtained in... 

This paper proposes an integrated integer nonlinear programming model for a concurrent cell formation and production planning problem in a dynamic cell-manufacturing system (DCMS) with limited resources to setup cells and to procure machines. The proposed model seeks to minimise the total costs associated with the production planning and the cell construction and formation under a dynamic system. To validate the model, it is first converted to a linear programming. Then, a numerical example is presented based on which the branch and bound method is used to solve it employing the Lingo 8 software. Besides, due to NP-hardness of the problem, two meta-heuristic algorithms namely a GA and a PSO... 

In this study, we introduce a multivariate gamma distribution, then, by defining a new statistic, three control charts called the MG charts, are proposed for this distribution. The first control chart is based on the exact distribution of this statistic, the second control chart is based on the Satterthwaite approximation, and the last is based on the normal approximation. The efficiency of the proposed control charts is evaluated by the average run length (ARL) criterion. The results show that whenever the magnitude of the parameter shifts c<1, the control chart based on the exact distribution has smaller ARL1s, while for c>1, the control chart based on Satterthwaite approximation show...