scholarly journals Optimizing Centralized Dispatching of Flexible Feeder Transit considering Transfer Coordination with Regular Public Transit

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yu-Qiong Wang ◽  
Shun-Ping Jia ◽  
Run-Bin Wei ◽  
Min Wang
Keyword(s):  
Delay Time ◽  
Public Transit ◽  
Optimal Solution ◽  
Optimal Operation ◽  
Operating Costs ◽  
Response Ratio ◽  
Proposed Model ◽  
Feeder Transit ◽  
The One ◽  
Transfer Services

Optimizing centralized dispatching of flexible feeder transit to provide transport and transfer services is important and theoretically challenging for real-world applications. Considering transfer coordination with regular public transit, a multiobjective optimization model that can output an operation plan containing vehicle routes and a timetable for a bus fleet is proposed. By establishing constraints for parameters such as maximum acceptable advance or delay time of transfer, rated passenger capacity, and maximum travel time of a single trip, the proposed model attempts to maximize the successful response ratio, minimize the passengers’ average time costs, and minimize the operating costs of a single passenger. A genetic algorithm was designed to solve the optimal solution, and computational experiments were conducted in a residential area in Beijing. Results reveal that the proposed model and algorithm can be applied in the operation of flexible feeder transit. Moreover, compared with the distributed dispatching method, the value of the optimal objective function in the proposed model was improved by 26%. Although the successful response ratio showed a 29.3% increase and the average passenger time cost showed a small drop, the operating costs per passenger were reduced by 30.7%. The different weight coefficients of the subobjective function and maximum acceptable advance or delay time of transfer could result in different optimal operation plans. Essentially, the optimization procedures for the successful response ratio and the operating costs are in the same direction, whereas the one for the passenger’ cost is in the opposite direction. However, operators should select appropriate values to optimize operation plans.

scholarly journals Optimal Operation of the Campus Microgrid considering the Resource Uncertainty and Demand Response Schemes

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Hafiz Abd ul Muqeet ◽  
Hafiz Mudassir Munir ◽  
Aftab Ahmad ◽  
Intisar Ali Sajjad ◽  
Guang-Jun Jiang ◽  
...  
Keyword(s):  
Power Systems ◽  
Demand Response ◽  
Solar Irradiance ◽  
Distribution System ◽  
Energy Demand ◽  
Mathematical Problem ◽  
Optimal Solution ◽  
Optimal Operation ◽  
Mixed Integer ◽  
Proposed Model

Present power systems face problems such as rising energy charges and greenhouse gas (GHG) releases. These problems may be assuaged by participating distributed generators (DGs) and demand response (DR) policies in the distribution system (DS). The main focus of this paper is to propose an energy management system (EMS) approach for campus microgrid (µG). For this purpose, a Pakistani university has been investigated and an optimal solution has been proposed. Conventionally, it contains electricity from the national grid only as a supply to fulfil the energy demand. Under the proposed setup, it contains campus owned nondispatchable DGs such as solar photovoltaic (PV) panels and microturbines (MTs) as dispatchable sources. To overcome the random nature of solar irradiance, station battery has been integrated as energy storage. The subsequent nonlinear mathematical problem has been scheduled by mixed-integer nonlinear programming (MINLP) in MATLAB for saving energy cost and battery aging cost. The framework has been validated under deterministic and stochastic environments. Among random parameters, solar irradiance and load have been taken into consideration. Case studies have been carried out considering the demand response strategies to analyze the proposed model. The obtained results show that optimal management and scheduling of storage in the presence of DGs mutually benefit by minimizing consumption cost (customer) and grid load (utility) which show the efficacy of the proposed model. The results obtained are compared to the existing literature and a significant cost reduction is found.

Variable-Capacity Operations with Modular Transits for Shared-Use Corridors

2020 ◽  
Vol 2674 (9) ◽  
pp. 230-244
Author(s):  
Xiaowei Shi ◽  
Zhiwei Chen ◽  
Mingyang Pei ◽  
Xiaopeng Li
Keyword(s):  
Programming Model ◽  
Optimal Solution ◽  
Operating Costs ◽  
Mixed Integer ◽  
Transit Systems ◽  
Persistent Problem ◽  
Proposed Model ◽  
Variable Capacity ◽  
New Perspective ◽  
In Transit

Since passenger demand in urban transit systems is asymmetrically distributed across different periods in a day and different geographic locations across the cities, the tradeoff between vehicle operating costs and service quality has been a persistent problem in transit operational design. The emerging modular vehicle technology offers us a new perspective to solve this problem. Based on this concept, we propose a variable-capacity operation approach with modular transits for shared-use corridors, in which both dispatch headway and vehicle capacity are decision variables. This problem is rigorously formulated as a mixed integer linear programming model that aims to minimize the overall system cost, including passenger waiting time costs and vehicle operating costs. Because the proposed model is linear, the state-of-the-art commercial solvers (e.g., Gurobi) can be used to obtain the optimal solution of the investigated problem. With numerical experiments, we demonstrate the feasibility of the mathematical model, verify the effectiveness of the proposed model in reducing overall system costs in transit systems, as well as the robustness of the proposed model with different parameter settings.

A Relativistic Newtonian Mechanics Predicts with Precision the Results of Recent Neutrino-Velocity Experiments

2014 ◽  
Vol 6 (1) ◽  
pp. 1032-1035 ◽  
Author(s):  
Ramzi Suleiman
Keyword(s):  
Null Hypothesis ◽  
Experimental Studies ◽  
Theoretical Models ◽  
Newtonian Mechanics ◽  
Speed Of Light ◽  
Symmetry Principle ◽  
Proposed Model ◽  
Significant Difference ◽  
The One ◽  
Complete Collapse

The research on quasi-luminal neutrinos has sparked several experimental studies for testing the "speed of light limit" hypothesis. Until today, the overall evidence favors the "null" hypothesis, stating that there is no significant difference between the observed velocities of light and neutrinos. Despite numerous theoretical models proposed to explain the neutrinos behavior, no attempt has been undertaken to predict the experimentally produced results. This paper presents a simple novel extension of Newton's mechanics to the domain of relativistic velocities. For a typical neutrino-velocity experiment, the proposed model is utilized to derive a general expression for . Comparison of the model's prediction with results of six neutrino-velocity experiments, conducted by five collaborations, reveals that the model predicts all the reported results with striking accuracy. Because in the proposed model, the direction of the neutrino flight matters, the model's impressive success in accounting for all the tested data, indicates a complete collapse of the Lorentz symmetry principle in situation involving quasi-luminal particles, moving in two opposite directions. This conclusion is support by previous findings, showing that an identical Sagnac effect to the one documented for radial motion, occurs also in linear motion.

Drug Target Group Prediction with Multiple Drug Networks

2020 ◽  
Vol 23 (4) ◽  
pp. 274-284 ◽  
Author(s):  
Jingang Che ◽  
Lei Chen ◽  
Zi-Han Guo ◽  
Shuaiqun Wang ◽  
Aorigele
Keyword(s):  
Drug Target ◽  
Low Cost ◽  
Machine Learning Algorithms ◽  
Classification Model ◽  
Support Vector ◽  
Multiple Drug ◽  
Property A ◽  
Multiple Networks ◽  
Proposed Model ◽  
The One

Background: Identification of drug-target interaction is essential in drug discovery. It is beneficial to predict unexpected therapeutic or adverse side effects of drugs. To date, several computational methods have been proposed to predict drug-target interactions because they are prompt and low-cost compared with traditional wet experiments. Methods: In this study, we investigated this problem in a different way. According to KEGG, drugs were classified into several groups based on their target proteins. A multi-label classification model was presented to assign drugs into correct target groups. To make full use of the known drug properties, five networks were constructed, each of which represented drug associations in one property. A powerful network embedding method, Mashup, was adopted to extract drug features from above-mentioned networks, based on which several machine learning algorithms, including RAndom k-labELsets (RAKEL) algorithm, Label Powerset (LP) algorithm and Support Vector Machine (SVM), were used to build the classification model. Results and Conclusion: Tenfold cross-validation yielded the accuracy of 0.839, exact match of 0.816 and hamming loss of 0.037, indicating good performance of the model. The contribution of each network was also analyzed. Furthermore, the network model with multiple networks was found to be superior to the one with a single network and classic model, indicating the superiority of the proposed model.

scholarly journals Wind Farm Cable Connection Layout Optimization with Several Substations

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3615
Author(s):  
Adelaide Cerveira ◽  
Eduardo J. Solteiro Pires ◽  
José Baptista
Keyword(s):  
Energy Production ◽  
Wind Farm ◽  
Programming Model ◽  
Optimal Solution ◽  
Wind Farms ◽  
Green Energy ◽  
Fossil Energy ◽  
Proposed Model ◽  
Short Time ◽  
Cable Connection

Green energy has become a media issue due to climate changes, and consequently, the population has become more aware of pollution. Wind farms are an essential energy production alternative to fossil energy. The incentive to produce wind energy was a government policy some decades ago to decrease carbon emissions. In recent decades, wind farms were formed by a substation and a couple of turbines. Nowadays, wind farms are designed with hundreds of turbines requiring more than one substation. This paper formulates an integer linear programming model to design wind farms’ cable layout with several turbines. The proposed model obtains the optimal solution considering different cable types, infrastructure costs, and energy losses. An additional constraint was considered to limit the number of cables that cross a walkway, i.e., the number of connections between a set of wind turbines and the remaining wind farm. Furthermore, considering a discrete set of possible turbine locations, the model allows identifying those that should be present in the optimal solution, thereby addressing the optimal location of the substation(s) in the wind farm. The paper illustrates solutions and the associated costs of two wind farms, with up to 102 turbines and three substations in the optimal solution, selected among sixteen possible places. The optimal solutions are obtained in a short time.

Modeling Capacity of Through Movement at Signalized Intersection Affected by Short Left-Turn Bay under Different Signal Settings

2021 ◽  
pp. 036119812110064
Author(s):  
Zihang Wei ◽  
Yunlong Zhang ◽  
Xiaoyu Guo ◽  
Xin Zhang
Keyword(s):  
Cycle Length ◽  
Signalized Intersections ◽  
Signalized Intersection ◽  
Essential Factor ◽  
Highway Capacity ◽  
Left Turn ◽  
Highway Capacity Manual ◽  
Proposed Model ◽  
Vehicle Demand ◽  
The One

Through movement capacity is an essential factor used to reflect intersection performance, especially for signalized intersections, where a large proportion of vehicle demand is making through movements. Generally, left-turn spillback is considered a key contributor to affect through movement capacity, and blockage to the left-turn bay is known to decrease left-turn capacity. Previous studies have focused primarily on estimating the through movement capacity under a lagging protected only left-turn (lagging POLT) signal setting, as a left-turn spillback is more likely to happen under such a condition. However, previous studies contained assumptions (e.g., omit spillback), or were dedicated to one specific signal setting. Therefore, in this study, through movement capacity models based on probabilistic modeling of spillback and blockage scenarios are established under four different signal settings (i.e., leading protected only left-turn [leading POLT], lagging left-turn, protected plus permitted left-turn, and permitted plus protected left-turn). Through microscopic simulations, the proposed models are validated, and compared with existing capacity models and the one in the Highway Capacity Manual (HCM). The results of the comparisons demonstrate that the proposed models achieved significant advantages over all the other models and obtained high accuracies in all signal settings. Each proposed model for a given signal setting maintains consistent accuracy across various left-turn bay lengths. The proposed models of this study have the potential to serve as useful tools, for practicing transportation engineers, when determining the appropriate length of a left-turn bay with the consideration of spillback and blockage, and the adequate cycle length with a given bay length.

scholarly journals An Alternative Promotion Time Cure Model with Overdispersed Number of Competing Causes: An Application to Melanoma Data

Mathematics ◽  
2021 ◽  
Vol 9 (15) ◽  
pp. 1815
Author(s):  
Diego I. Gallardo ◽  
Mário de Castro ◽  
Héctor W. Gómez
Keyword(s):  
Estimation Method ◽  
Selection Criterion ◽  
Likelihood Method ◽  
Simulation Studies ◽  
Cure Rate ◽  
Nested Models ◽  
Proposed Model ◽  
The Em Algorithm ◽  
Competing Causes ◽  
The One

A cure rate model under the competing risks setup is proposed. For the number of competing causes related to the occurrence of the event of interest, we posit the one-parameter Bell distribution, which accommodates overdispersed counts. The model is parameterized in the cure rate, which is linked to covariates. Parameter estimation is based on the maximum likelihood method. Estimates are computed via the EM algorithm. In order to compare different models, a selection criterion for non-nested models is implemented. Results from simulation studies indicate that the estimation method and the model selection criterion have a good performance. A dataset on melanoma is analyzed using the proposed model as well as some models from the literature.

scholarly journals Adaptive model to support business process reengineering

2021 ◽  
Vol 7 ◽  
pp. e505
Author(s):  
Noha Ahmed Bayomy ◽  
Ayman E. Khedr ◽  
Laila A. Abd-Elmegid
Keyword(s):  
Business Process ◽  
Success Factors ◽  
Business Processes ◽  
Business Environment ◽  
Process Time ◽  
Critical Success ◽  
Proposed Model ◽  
Before And After ◽  
Time Cycle ◽  
The One

The one constant in the world is change. The changing dynamics of business environment enforces the organizations to re-design or reengineer their business processes. The main objective of such reengineering processes is to provide services or produce products with the possible lowest cost, shortest time, and best quality. Accordingly, Business Process Re-engineering (BPR) provides a roadmap of how to efficiently achieve the operational goals in terms of enhanced flexibility and productivity, reduced cost, and improved quality of service or product. In this article, we propose an efficient model for BPR. The model specifies where the breakdowns occur in BPR implementation, justifies why such breakdowns occur, and proposes techniques to prevent their occurrence again. The proposed model has been built based on two main sections. The first section focuses on integrating Critical Success Factors (CSFs) and the performance of business processes during the reengineering processes. Additionally, it implements the association rule mining technique to investigate the relationship between CSFs and different business processes. The second section aims to measure the performance of business processes (intended success of BPR) by process time, cycle time, quality and cost before and after reengineering processes. A case study of the Egyptian Tax Authority (ETA) is used to test the efficiency of the proposed model.

scholarly journals Automation of the one-storey underground parking space organization

2021 ◽  
Vol 284 ◽  
pp. 06012
Author(s):  
Natalia Knyazeva ◽  
Anastasia Kolosova
Keyword(s):  
Evolutionary Algorithms ◽  
Urban Area ◽  
Optimal Solution ◽  
Parking Space ◽  
Space Planning ◽  
Parking Lots ◽  
Legal Documents ◽  
Space Organization ◽  
Big Cities ◽  
The One

With the growing car population in big cities, the problem of its keeping in conditions of a compact urban area has happened. The organisation of parking space in a different way has resolved this issue. Underground parking was in demand in many countries even in the XX century. By the way, they are becoming more and more popular now. The design of car parking is based on legal documents, which regulate the size of car parking seats and the width of the passage inside the garage. It is expedient to use evolutionary algorithms as one of the tools of algorithmic modelling for automation of design the car parking lots and for identifying the most effective and profitable way of the car parking space planning. So, the process of looking for the most optimal solution in underground car parking designing.

Impact of Automated Vehicles on Optimal Demand-Responsive Feeder Transit Network Design

2021 ◽  
Vol 2 (1) ◽  
pp. 84-100
Author(s):  
Amirreza Nickkar ◽  
Young-Jae Lee ◽  
Seyedehsan Dadvar
Keyword(s):  
Economic Benefits ◽  
Operating Costs ◽  
Transit Systems ◽  
Travel Costs ◽  
Bus Routing ◽  
Routing Optimization ◽  
Passenger Travel ◽  
Feeder Bus ◽  
Feeder Transit ◽  
Transit Network Design

This article aims to examine the economic benefits of automating flexible demand responsive feeder transit systems using a developed feeder bus routing optimization algorithm. The objective function of the algorithm is to minimize total passengers' and operating costs of the system. The results showed that when unit operating costs decline, total operating costs, and total costs obviously decline. Furthermore, when unit operating costs decline, the average passenger travel distance and total passenger travel costs decline while the ratio of total operating costs per unit operating costs increases. That means if unit operating costs decrease, the portion of passenger travel costs in the total costs increases, and the optimization process tends to reduce passenger costs more while reducing total costs. Assuming that automation of the vehicles reduces the operating costs, it will reduce not only total operating costs and total costs, but also total passenger travel costs.

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