in this paper, integrated direct and reverse logistics considering production, distribution, customer, devastation, retrieval centers under uncertainty are developed. in this model, cost parameters are not certain, thus the scenario-based robust optimization method is applied. the aim of this model is to minimize the total cost and obtain a robust solution. finally, a practical case study is pr...

The expansion of explainable artificial intelligence as a field research has generated numerous methods visualizing and understanding the black box machine learning model. Attribution maps are generally used to highlight parts input image that influence model make specific decision. On other hand, robustness models natural noise adversarial attacks is also being actively explored. This paper fo...

In this paper, we present a new idea for robust project scheduling combined with a cost-oriented uncertainty investigation. The result of the new approach is a makespan minimal robust proactive schedule, which is immune against the uncertainties in the activity durations and which can be evaluated from a cost-oriented point of view on the set of the uncertain-but-bounded duration and cost param...

Production planning and control (PPC) systems have to deal with rising complexity and dynamics. The complexity of planning tasks is due to some existing multiple variables and dynamic factors derived from uncertainties surrounding the PPC. Although literatures on exact scheduling algorithms, simulation approaches, and heuristic methods are extensive in production planning, they seem to be ineff...

Mendelian randomization (MR) is a popular instrumental variable (IV) approach, in which one or several genetic markers serve as IVs that can sometimes be leveraged to recover valid inferences about given exposure-outcome causal association subject unmeasured confounding. A key IV identification condition known the exclusion restriction states cannot have direct effect on outcome not mediated by...

This paper presents the design principles of sliding mode controller, which is implemented in coupled tank system. The Sliding Mode Control (SMC) controller exhibited a robust stability can overcome nonlinearities, reduce disturbances and noise that occur work start with mathematical modelling system using second order single input output (SISO) technique. Then, began by deriving surface accord...