Abstract: In the field of photoelectric devices, a visible light detector is provided with high-photoresponse based on a TiO2/MoS2 heterojunction and a preparation method thereof. The detector, based on a back-gated field-effect transistor based on MoS2, includes a MoS2 channel, a TiO2 modification layer, a SiO2 dielectric layer, Au source/drain electrodes and a Si gate electrode, The TiO2 modification layer is modified on the surface of the MoS2 channel. By employing micromechanical exfoliation and site-specific transfer of electrodes, the method is intended to prepare a detector by constructing a back-gated few-layer field-effect transistor based on MoS2, depositing Ti on the channel surface, and natural oxidation.

Abstract: A computer, for planning moves of freight using vehicles, determines one or more attributes of a mission, based on a group of shipments being consolidated into the mission, computes a total amount of freight to be moved, and decides on feasibility of performing the mission, using a vehicle of a given type based at least on each of (A) the amount of freight, (B) one or more attributes of the mission, and (C) multiple effective capacities of freight moveable by the type of vehicle being selected, which depend on the mission attribute(s). Multiple effective capacities for each vehicle type, and corresponding values of mission attribute(s) at which they are to be applied are stored in the computer ahead of time, based on industry experience. Examples of mission attribute(s) include (1) number of stops, (2) type of stops (whether pooling or not), and (3) a combination thereof.

Abstract: Systems, methods, and machine-readable media are disclosed to allocating inventory across a plurality of locations in a supply chain. In one embodiment, a method comprises determining a total time-phased inventory and target safety stock level for each of the items at each location based on the baseline inventory as determined from expected demand and lead times for each item at each location, a target service level, a demand uncertainty level, a lead time uncertainty level, carrying costs in the supply chain and user constraints on budget, capacity and inventory.

Abstract: A computer, for planning moves of freight automatically adds one or more layover(s) to a mission. Next, the computer determines one or more charge(s) for the layovers, using carriers' rules. Thereafter, the computer uses the charge(s) in deciding whether to include the mission in a transportation plan to be executed. In some embodiments, the computer automatically maintains, for the given mission, counts of attributes on which limits are imposed by a government or by carriers, such as driving time, on-duty time, and driving distance, and when any count exceeds a corresponding limit in the midst of a driving activity, the computer automatically divides up the current driving activity into a truncated driving activity and a remainder driving activity, separated by a layover activity. The computer also determines an estimated time of arrival, including the impact of required layovers, to reach destination(s), and whether layover(s) is/are required at the destination(s), e.g.

Abstract: Example systems, methods, computer-readable media, software, and other embodiments are described herein that relate to optimizing carrier selection for a transportation planning system. In one embodiment, given a set of trips that have been defined to transport a set of configured loads, a carrier selection logic can be provided that is configured to analyze the set of trips and attempt to repair or cure one or more constraint violations that may exist in one or more of the trips. For example, the repair may include attempting to reassign a carrier (e.g. carrier/service/vehicle type) that is assigned to a trip to a different carrier in order to reduce overall constraint violations for the set of trips and may reduce the overall global cost for the set of trips.

Abstract: Systems, methodologies, media, and other embodiments associated with transportation planning in light of drop trailer arrangements are described. One exemplary computer-implemented method embodiment includes receiving orders that describe items to be delivered to facilities as controlled by order requirements. The method may also include accessing a transportation planning model that includes information concerning shipping modes and carriers by which an order can be delivered to a facility. The transportation planning model may also include data concerning drop trailer arrangements between facilities and the carriers. The method may also include selectively consolidating orders into shipments based on the transportation planning model and the availability of a drop trailer arrangement. The method may also include selectively assigning shipments to loads based on the transportation planning model and the availability of a drop trailer action.

Abstract: Systems, methods, and machine-readable media are disclosed to allocating inventory across a plurality of locations in a supply chain. In one embodiment, a method comprises determining a total time-phased inventory and target safety stock level for each of the items at each location based on the baseline inventory as determined from expected demand and lead times for each item at each location, a target service level, a demand uncertainty level, a lead time uncertainty level, carrying costs in the supply chain and user constraints on budget, capacity and inventory.

Abstract: A computer, for planning moves of freight automatically adds one or more layover(s) to a mission. Next, the computer determines one or more charge(s) for the layovers, using carriers' rules. Thereafter, the computer uses the charge(s) in deciding whether to include the mission in a transportation plan to be executed. In some embodiments, the computer automatically maintains, for the given mission, counts of attributes on which limits are imposed by a government or by carriers, such as driving time, on-duty time, and driving distance, and when any count exceeds a corresponding limit in the midst of a driving activity, the computer automatically divides up the current driving activity into a truncated driving activity and a remainder driving activity, separated by a layover activity. The computer also determines an estimated time of arrival, including the impact of required layovers, to reach destination(s), and whether layover(s) is/are required at the destination(s), e.g.

Abstract: A computer, for planning moves of freight using vehicles, determines one or more attributes of a mission, based on a group of shipments being consolidated into the mission, computes a total amount of freight to be moved, and decides on feasibility of performing the mission, using a vehicle of a given type based at least on each of (A) the amount of freight, (B) one or more attributes of the mission, and (C) multiple effective capacities of freight moveable by the type of vehicle being selected, which depend on the mission attribute(s). Multiple effective capacities for each vehicle type, and corresponding values of mission attribute(s) at which they are to be applied are stored in the computer ahead of time, based on industry experience. Examples of mission attribute(s) include (1) number of stops, (2) type of stops (whether pooling or not), and (3) a combination thereof.

Abstract: Systems, methodologies, media, and other embodiments associated with multi-level pooling in transportation planning are described. One exemplary method embodiment includes, co-operatively and in parallel choosing pooling points and order-legs to consolidate. The example method may also include constructing a cost-optimal trip based, at least in part, on the contemporaneously chosen pooling points and orders-legs.

Abstract: Example systems, methods, computer-readable media, software, and other embodiments are described herein that relate to optimizing carrier selection for a transportation planning system. In one embodiment, given a set of trips that have been defined to transport a set of configured loads, a carrier selection logic can be provided that is configured to analyze the set of trips and attempt to repair or cure one or more constraint violations that may exist in one or more of the trips. For example, the repair may include attempting to reassign a carrier (e.g. carrier/service/vehicle type) that is assigned to a trip to a different carrier in order to reduce overall constraint violations for the set of trips and may reduce the overall global cost for the set of trips.

Abstract: Systems, methodologies, media, and other embodiments associated with parallel optimization in transportation planning are described. One exemplary method embodiment may include selecting, in parallel, candidate loads to satisfy a set of orders, selecting final loads from the candidate loads, and in parallel selectively manipulating the final loads into a transportation plan that reduces a transportation cost.

Abstract: Systems, methodologies, media, and other embodiments associated with transportation planning with multi-level firming are described. One exemplary computer-implemented method embodiment includes accessing transportation planning elements and a transportation planning model. The method may also include identifying loads that satisfy orders in the transportation planning elements according to constraints in the transportation planning model and then applying multi-level firming designations to transportation planning elements related to the identified loads. The method may also include identifying additional loads based, at least in part, on the multi-level firming designations. The method may output an actionable plan of loads stored, for example, on a computer-readable medium.

Abstract: Systems, methodologies, media, and other embodiments associated with transportation planning in light of drop trailer arrangements are described. One exemplary computer-implemented method embodiment includes receiving orders that describe items to be delivered to facilities as controlled by order requirements. The method may also include accessing a transportation planning model that includes information concerning shipping modes and carriers by which an order can be delivered to a facility. The transportation planning model may also include data concerning drop trailer arrangements between facilities and the carriers. The method may also include selectively consolidating orders into shipments based on the transportation planning model and the availability of a drop trailer arrangement. The method may also include selectively assigning shipments to loads based on the transportation planning model and the availability of a drop trailer action.