the paper discusses the location-allocation model for logistic networks and distribution centers through considering uncertain parameters. in real-world cases, demands and transshipment costs change over the period of the time. this may lead to large cost deviation in total cost. scenario based robust optimization approaches are proposed where occurrence probability of each scenario is not know...

The purpose of this study is to investigate the accuracy of predictions of aniline removal efficiency in a moving bed biofilm reactor (MBBR) by various methods, namely by RBF, ANFIS, and fuzzy regression analysis. The reactor was operated in an aerobic batch and was filled by light expanded clay aggregate (LECA) as a carrier for the treatment of Aniline synthetic wastewater. Exploratory data an...

The traditional deterministic day-ahead (DA) market clearing does not accommodate the uncertainty from variable renewable energy sources, resulting in an increasing activation of expensive reserves and curtailment events. Robust optimization (RO) has been proposed to mitigate this uncertainty. However, as RO considers worst-case scenarios, it results highly conservative solutions. This paper pr...

An optical unitary converter (OUC) that can convert a set of $N$ mutually orthogonal modes into another arbitrary is expected to be key device in diverse applications, including communication, deep learning, and quantum computing. While various types OUC have been demonstrated on photonic integration platforms, the sensitivity against slight deviation waveguide dimensions has crucial issue scal...

This paper presents a robust vision system for lighting fluctuation for a parts positioning robot by means of dynamic range expansion of a video camera. The vision system was confirmed by experiments to stably detect the position of the object, in comparison to a conventional method, even if the light environment dynamically varies. The above result revealed that the dynamic range expansion of ...