Data envelopment analysis (DEA) is an approach to measure the relative efficiency of decision-making units with multiple inputs and multiple outputs using mathematical programming. In the traditional DEA, it is assumed that we know the input or output role of each performance measure. But in some situations, the type of performance measure is unknown. These performance measures are called flexi...

Data Envelopment Analysis (DEA) deals with evaluating a set of decision-making units (DMUs) based on nonparametric mathematical approaches. In classical DEA models, the given set of factors of DMUs is divided into two categories, inputs and outputs, while in some practical problems there are some measures whose membership to these categories is unclear. It means these factors treat different in...

In conventional DEA, measures are classified as either input or output. However, in some real cases there are variables whose status is not known as input or output before assessment. These variable are known as flexible measures. One of the most important economic dimensions for ensuring the success of a company is the efficiency with which it uses its resources. Therefore, centering on Asses...

in this paper, an exact geometric algorithm is presented for solving two-job sequencing and scheduling problems in flexible flow shop and job shop environments while the resources are (un)available in some time periods and processors (un)availability is the same in all work centers. this study seems utterly new and it is applicable to any performance measure based on the completion time. the in...

In this paper, we consider a newsvendor who is going to invest on dedicated or flexible capacity, our goal is to find the optimal investment policy to maximize total profit while the newsvendor faces uncertainty in lead time and demand simultaneously. As highlighted in literature, demand is stochastic, while lead time is constant. However, in reality lead time uncertainty decreases newsvendor's...