This paper discusses an on-line Tasks Assignment and Routing Problem (TARP) for Autonomous Transportation Systems (ATSs) in manufacturing systems. The TARP is a constrained version of the Pickup and Delivery Problem with Time Windows (PDPTW). In our former study, a cooperative algorithm, called the triple loop method, with autonomous distributed agents has been proposed. The Improving initial Task Assignment and Avoiding Deadlock method (ITAAD) is a faster algorithm than the triple loop method. In this paper, we propose a new vehicle routing method for the ITAAD. Results of computational experiments show effectiveness of the proposed routing method.

In multi-hop wireless networks, communication quality depends on the selection of a path between source and destination nodes from several candidate paths. Exploring how path selection affects communication quality is important to characterize the best path. To do this, in [1], we used expected transmission count (ETX) as a metric of communication quality and theoretically characterized minimum route ETX, which is the ETX of the best path, in a static one-dimensional random multi-hop network. In this paper, we characterize minimum route ETX in static two-dimensional multi-hop networks. We give the exact formula of minimum route ETX in a two-dimensional network, assuming that nodes are located with lattice structure and that the ETX function satisfies three conditions for simplifying analysis. This formula can be used as an upper bound of minimum route ETX without two of the three conditions. We show that this upper bound is close to minimum route ETX by comparing it with simulation results. Before deriving the formula, we also give the formula for a one-dimensional network where nodes are located at constant intervals. We also show that minimum route ETX in the lattice network is close to that in a two-dimensional random network if the node density is large, based on a comparison between the numerical and simulation results.

We present a new method called the slope nucleation method (SNM) for the growth of high-quality organic 4-dimethylamino-N-methyl-4-stilbazolium tosylate (DAST) crystals. The SNM features the ability to control the nucleation position and the growth orientation of DAST crystals in spontaneous nucleated growth. X-ray diffraction (XRD) rocking curve measurements indicate that the SNM is effective for obtaining high-quality DAST crystals as compared to conventional spontaneous nucleation methods. We evaluated the electro-optic (EO) properties of DAST crystals by an external EO probing technique because DAST crystals are expected to be used in transverse-field probing. DAST crystals exhibits nearly five-times EO sensitivity enhancement as compared to inorganic KTiOPO4 (KTP) crystals at 90 kHz. The larger EO signal power obtained from the DAST crystal was almost constant at low frequencies (30 Hz to 90 kHz), whereas the KTP crystal could not respond below 180 Hz. We also observed excellent signals at all measured points due to the improved crystallinity of the crystal grown by the SNM.

The characteristics of HfO2 gate stacks, which consisted of the SiN layer deposited between the HfO2 and poly-Si gate electrode and the SiON interfacial layer were investigated. The SiN layer played important role to reduce the leakage current caused by the defect of the crystallized HfO2. The SiN layer was also effective to achieve the prevention of the interfacial reaction, the suppression of dopant penetration. Furthermore, that stack structure indicated excellent TDDB reliability fabricated by conventional high temperature processes.

This paper discusses an on-line Tasks Assignment and Routing Problem (TARP) for Autonomous Transportation Systems (ATSs) in manufacturing systems. The TARP results in a constrained version of the Pickup and Delivery Problem with Time Windows (PDPTW). As an approach to this problem, a cooperative algorithm with autonomous distributed agents has been proposed. The algorithm is able to plan deadlock-free routes even though the buffer capacity is less, but includes reformability at the point that computation time of that case increases drastically. This paper proposes an initial task assignment method to reduce computation time on planning routes. Results of computational experiments show effectiveness of the proposed method.