In this study, the performance of the algorithms of whale, Differential evolutionary, crow search, and Gray Wolf optimization were evaluated to operate the Golestan Dam reservoir with the objective function of meeting downstream water needs. Also, after defining the objective function and its constraints, the convergence degree of the algorithms was compared with each other and with the absolut...

In recent years, research on modeling in both the philosophy of science and the social studies of science and technology has undergone an acute transformation. Philosophers and social scientists have begun to realize that science, in the words of Carrier and Nordmann, has increasingly shifted its focus from “epistemic or truthoriented” research to “application-dominated” research. “Science is v...

Data envelopment analysis is a method for evaluating the relative efficiency of a collection of decision making units. The DEA classic models calculate each unit’s efficiency in the best condition, meaning that finds a weight that the DMU is at its maximum efficiency. In this paper, utilizing the directional distance function model in the presence of undesirable outputs, the efficiency of each ...

the ways of placing decision making units (dmus) in certain clusters are found as a subject in statistics, these ways usually are heuristic. the proposed clustering approach in this article considers preferences of dmus. this study applies data envelopment analysis (dea) dmus are clustered by solving multi-objective linear problem (molp) and by considering preferences of each dmu at production ...

data envelopment analysis (dea) measures the relative efficiency of decision making units (dmus) with multiple inputs and multiple outputs. dea-based malmquist productivity index measures the productivity change over time. we propose a dynamic dea model involving network structure in each period within the framework a dea. we have previously published the network dea (ndea) and the dynamic dea ...