Direct Observation of Carrier Transportation Process in InGaAs/GaAs Multiple Quantum Wells Used for Solar Cells and Photodetectors

The resonant excitation is used to generate photo-excited carriers in quantum wells to observe the process of the carriers transportation by comparing the photoluminescence results between quantum wells with and without a p-n junction. It is observed directly in experiment that most of the photo-excited carriers in quantum wells with a p-n junction escape from quantum wells and form photoeurrent rather than relax to the ground state of the quantum wells. The photo absorption coei^cient of multiple quantum wells is also enhanced by a p-n junction. The results pave a novel way for solar cells and photodetectors making use of low-dimensional structure.

Active dynamic pre-protection mechanism for MPLS-TP network

The active-fault-alarm （AFA） technologies and the dynamic protection mechanism of the optical network controlled by the multi-protocol label switching transport profile （MPLS-TP） are both studied in this article. On this basis, an active dynamic pre-protection （ADPP） mechanism is proposed. This active dynamic pre-protection mechanism is allowed to establish a so called temporary protection path （TPP） for the work path before a potential fault occurs and to switch to TPP only after the fault occurs. It keeps the TPP flexibly only when it is in low- quality or fault state to realize dynamic protection even better and to achieve better resource utilization. Simulation results show that the proposed new mechanism has better performance in terms of the flexibility and the efficiency from the perspective of time.

An evolutionary algorithm approach for the constrained multi-depot vehicle routing problem

Purpose-The purpose of this paper is to explore a real world vehicle routing problem(VRP)that has multi-depot subcontractors with a heterogeneous fleet of vehicles that are available to pickup/deliver jobs with varying time windows and locations.Both the overall job completion time and number of drivers utilized are analyzed for the automated job allocations and manual job assignments from transportation field experts.Design/methodology/approach-A nested genetic algorithm(GA)is used to automate the job allocation process and minimize the overall time to deliver all jobs,while utilizing the fewest number of drivers-as a secondary objective.Findings-Three different real world data sets were used to compare the results of the GA vs transportation field experts’manual assignments.The job assignments from the GA improved the overall job completion time in 100 percent(30/30)of the cases and maintained the same or fewer drivers as BS Logistics(BSL)in 47 percent(14/30)of the cases.Originality/value-This paperprovidesa novel approach to solving a real world VRPthathasmultiple variants.While there have been numerous models to capture a select number of these variants,the value of this nested GA lies in its ability to incorporate multiple depots,a heterogeneous fleet of vehicles as well as varying pickup times,pickup locations,delivery times and delivery locations for each job into a single model.Existing research does not provide models to collectively address all of these variants.