Train Planning on a Single Track Shared-Use Passenger and Freight Corridor With Demand Considerations

2014 ◽  
Author(s):  
Ahmadreza Talebian ◽  
Bo Zou
Keyword(s):  
Marginal Cost ◽  
Mathematical Formulation ◽  
Computation Time ◽  
Search Space ◽  
Computational Effort ◽  
Scheduling Problem ◽  
Sequential Approach ◽  
Train Scheduling ◽  
Passenger Train ◽  
Passenger Trains

While the train scheduling problem has been investigated for an extended period of time, shared passenger and freight corridor planning and capacity analysis have gained growing attention recently, due largely to the emergence of higher speed rail lines in the US. This study proposes an integrated, hypergraph-based approach that considers constraints from infrastructure supply as well as passenger demand in solving the train scheduling problem on a passenger-freight shared rail corridor. Two approaches are proposed to capture different policies which could be implemented in real world. The first, sequential approach considers passenger train priority in schedule planning, and then develop freight trains schedules given the fixed schedule of passenger trains. In the second approach, we minimize the total costs of freight and passenger trains simultaneously. Our results indicates that the marginal cost increase for freight railroad due to considering passenger train priority is larger than the associated marginal cost reduction for passengers. We also find that using high resolution time units in the mathematical formulation does not significantly improve the solution, meanwhile causing substantial increase in computation time. Therefore we suggest choosing coarser a time unit to first generate an approximate solution, which is subsequently used to reduce the search space for feasible train schedules using a finer-grained time unit. We show that this considerably saves computational effort.

scholarly journals Train-Scheduling Optimization Model for Railway Networks with Multiplatform Stations

2019 ◽  
Vol 12 (1) ◽  
pp. 257
Author(s):  
Gianmarco Garrisi ◽  
Cristina Cervelló-Pastor
Keyword(s):  
Mathematical Formulation ◽  
Computation Time ◽  
Mixed Integer ◽  
Initial Population ◽  
Mixed Integer Linear Program ◽  
Transit System ◽  
Train Scheduling ◽  
Railway Networks ◽  
Np Hard Problem ◽  
Problem Instances

This paper focuses on optimizing the schedule of trains on railway networks composed of busy complex stations. A mathematical formulation of this problem is provided as a Mixed Integer Linear Program (MILP). However, the creation of an optimal new timetable is an NP-hard problem; therefore, the MILP can be solved for easy cases, computation time being impractical for more complex examples. In these cases, a heuristic approach is provided that makes use of genetic algorithms to find a good solution jointly with heuristic techniques to generate an initial population. The algorithm was applied to a number of problem instances producing feasible, though not optimal, solutions in several seconds on a laptop, and compared to other proposals. Some improvements are suggested to obtain better results and further improve computation time. Rail transport is recognized as a sustainable and energy-efficient means of transport. Moreover, each freight train can take a large number of trucks off the roads, making them safer. Studies in this field can help to make railways more attractive to travelers by reducing operative cost, and increasing the number of services and their punctuality. To improve the transit system and service, it is necessary to build optimal train scheduling. There is an interest from the industry in automating the scheduling process. Fast computerized train scheduling, moreover, can be used to explore the effects of alternative draft timetables, operating policies, station layouts, and random delays or failures.

scholarly journals Path Planning for an HEXA Parallel Mechanism using a Modified PSO Algorithm

2021 ◽  
Author(s):  
Lucian Milica ◽  
Adina Milica
Keyword(s):  
Parallel Mechanism ◽  
Characteristic Point ◽  
Hermite Polynomials ◽  
Mathematical Formulation ◽  
Pso Algorithm ◽  
Search Space ◽  
Computational Effort ◽  
Hermite Functions ◽  
End Effector ◽  
Modified Pso

Abstract This paper presents a method for determining the optimal trajectory of the characteristic point based on the kinematic analysis of a HEXA parallel mechanism. The optimization was performed based on a modified PSO algorithm based on Hermite polynomials (MH-PSO). The change made to the initial algorithm consists in restricting the search space of the solutions by using the Hermite polynomial expressions of the geometric parameters as time functions for defining the movements of the end-effector. The MH-PSO algorithm, from its inception, ensures a faster convergence of solutions and ease of computational effort and is the main advantage of the method presented. During the optimization process, the function followed was the length of the trajectory described by the sequence of positions of the characteristic point, belonging to the end effector element, in compliance with additional conditions imposed. The use of the Hermite functions and PSO algorithm leads to minimal effort for analysis and mathematical formulation of the optimization problem.

Shared Corridors, Shared Interests

2011 ◽  
Author(s):  
Allan M. Zarembski ◽  
James Blaze ◽  
Pradeep Patel
Keyword(s):  
High Speed ◽  
Safety Issue ◽  
Surface Profile ◽  
Physical Property ◽  
Passenger Train ◽  
Track Geometry ◽  
Track Maintenance ◽  
Trade Offs ◽  
Passenger Trains ◽  
Grade Crossings

What are some of the practical obstacles to a “shared interests” between a freight railway business and the proposed new higher speed passenger entity? This paper discusses the real “tension” between the two business interests that fund freight trains versus those that support and fund higher speed passenger trains as they attempt to share the same tracks in a safe manner. There are fundamental laws of physics that have to be addressed as the two different sets of equipment are “accommodated” on a shared corridor. This may not always be an easy accommodation between the two commercial parties. One real tension between the two commercial interests involves the physical problem of accommodating two radically different train sets on areas of curved track. For one example, what will be the passenger train required future higher speeds and how will these speeds be accommodated in existing main line tracks with curves varying from 1% to 6% in degrees? How much super elevation will need to be put back into the heretofore freight train tracks? How will the resulting super elevation affect the operation of so called drag or high tonnage slow speed bulk cargo trains? Accommodating such differences in train set types, axle loadings, freight versus passenger train set speeds, requires making detailed choices at the engineering level. These may be shared interests, but they are also variables with far different outcomes by design for the two different business types. The freight railways have spent the last few decades “taking the super elevation out” because it is not needed for the modern and highly efficient freight trains. Now the requirements of the passenger trains may need for it to be replaced. What are the dynamics and fundamental engineering principles at work here? Grade crossings have a safety issue set of interests that likely require such things as “quad” gates and for the highest passenger train speeds even complete grade separation. Track accommodating very high speed passenger trains requires under federal regulations much closer physical property tolerances in gauge width, track alignment, and surface profile. This in turn increases the level of track inspection and track maintenance expenses versus the standard freight operations in a corridor. Fundamentally, how is this all going to be allocated to the two different commercial train users? What will be the equally shared cost and what are examples of the solely allocated costs when a corridor has such different train users? In summary, this paper provides a description of these shared issues and the fundamental trade-offs that the parties must agree upon related to overall track design, track geometry, track curvature, super elevation options, allowed speeds in curves, more robust protection at grade crossings, and the manner in which these changes from the freight only corridors are to be allocated given the resulting much higher track maintenance costs of these to be shared assets.

A Novel Method of Coupling the Steam Turbine Exhaust Hood and the Last Stage Blades Using the Non-Linear Harmonic Method

2013 ◽  
Author(s):  
Zoe Burton ◽  
Grant Ingram ◽  
Simon Hogg
Keyword(s):  
Steam Turbine ◽  
Turbine Blades ◽  
Computation Time ◽  
Computational Effort ◽  
Alternative Methods ◽  
Test Case ◽  
Exhaust Hood ◽  
Harmonic Method ◽  
Non Linear ◽  
Last Stage

The exhaust hood of a steam turbine is a vital area of turbomachinery research its performance strongly influences the power output of the last stage blades. It is well known that accurate CFD simulations are only achieved when the last stage blades are coupled to the exhaust hood to capture the strong interaction. This however presents challenges as the calculation size grows rapidly when the full annulus is calculated. The size of the simulation means researchers are constantly searching of methods to reduce the computational effort without compromising solution accuracy. This work uses a novel approach, by coupling the last stage blades and exhaust hood by the Non-Linear Harmonic Method, a technique widely used to reduce calculation size in high pressure turbine blades and axial compressors. This has been benchmarked against the widely adopted Mixing Plane method. The test case used is the Generic Geometry, a representative exhaust hood and last stage blade geometry that is free from confidentiality and IP restrictions and for which first calculations were presented at last year’s conference [1]. The results show that the non-uniform exhaust hood inlet flow can be captured using the non-liner harmonic method, an effect not previously achievable with single passage coupled calculations such as the mixing plane approach. This offers a significant computational saving, estimated to be a quarter of the computation time compared with alternative methods of capturing the asymmetry with full annulus frozen rotor calculations.

scholarly journals Faster sequence alignment through GPU-accelerated restriction of the seed-and-extend search space

2014 ◽  
Author(s):  
Richard Wilton ◽  
Tamas Budavari ◽  
Ben Langmead ◽  
Sarah J Wheelan ◽  
Steven Salzberg ◽  
...  
Keyword(s):  
Sequence Alignment ◽  
High Throughput ◽  
Search Space ◽  
Computational Effort ◽  
Biological Sequences ◽  
Reduction Techniques ◽  
Software Implementations ◽  
List Processing ◽  
High Processing

Motivation: In computing pairwise alignments of biological sequences, software implementations employ a variety of heuristics that decrease the computational effort involved in computing potential alignments. A key element in achieving high processing throughput is to identify and prioritize potential alignments where high-scoring mappings can be expected. These tasks involve list-processing operations that can be efficiently performed on GPU hardware. Results: We implemented a read aligner called A21 that exploits GPU-based parallel sort and reduction techniques to restrict the number of locations where potential alignments may be found. When compared with other high-throughput aligners, this approach finds more high-scoring mappings without sacrificing speed or accuracy. A21 running on a single GPU is about 10 times faster than comparable CPU-based tools; it is also faster and more sensitive in comparison with other recent GPU-based aligners.

Performance Evaluation of Population Seeding Techniques of Permutation-Coded GA Traveling Salesman Problems Based Assessment

2021 ◽  
pp. 1074-1115
Author(s):  
Victer Paul ◽  
Ganeshkumar C ◽  
Jayakumar L
Keyword(s):  
Genetic Algorithms ◽  
Nearest Neighbor ◽  
Optimization Technique ◽  
Optimal Solution ◽  
Computation Time ◽  
Search Space ◽  
Population Based ◽  
Vital Role ◽  
Traveling Salesman ◽  
Performance Criteria

Genetic algorithms (GAs) are a population-based meta-heuristic global optimization technique for dealing with complex problems with a very large search space. The population initialization is a crucial task in GAs because it plays a vital role in the convergence speed, problem search space exploration, and also the quality of the final optimal solution. Though the importance of deciding problem-specific population initialization in GA is widely recognized, it is hardly addressed in the literature. In this article, different population seeding techniques for permutation-coded genetic algorithms such as random, nearest neighbor (NN), gene bank (GB), sorted population (SP), and selective initialization (SI), along with three newly proposed ordered-distance-vector-based initialization techniques have been extensively studied. The ability of each population seeding technique has been examined in terms of a set of performance criteria, such as computation time, convergence rate, error rate, average convergence, convergence diversity, nearest-neighbor ratio, average distinct solutions and distribution of individuals. One of the famous combinatorial hard problems of the traveling salesman problem (TSP) is being chosen as the testbed and the experiments are performed on large-sized benchmark TSP instances obtained from standard TSPLIB. The scope of the experiments in this article is limited to the initialization phase of the GA and this restricted scope helps to assess the performance of the population seeding techniques in their intended phase alone. The experimentation analyses are carried out using statistical tools to claim the unique performance characteristic of each population seeding techniques and best performing techniques are identified based on the assessment criteria defined and the nature of the application.

Damage Identification of Multimember Structure using Improved Neural Networks

2013 ◽  
Vol 3 (3) ◽  
pp. 57-75
Author(s):  
M. Rajendra ◽  
K. Shankar
Keyword(s):  
Damage Identification ◽  
Latin Hypercube Sampling ◽  
Search Space ◽  
Computational Effort ◽  
Frequency Change ◽  
The Novel ◽  
Damage Prediction ◽  
Rbf Network ◽  
Accuracy And Precision ◽  
Two Stages

A novel two stage Improved Radial Basis Function (IRBF) neural network for the damage identification of a multimember structure in the frequency domain is presented. The improvement of the proposed IRBF network is carried out in two stages. Conventional RBF network is used in the first stage for preliminary damage prediction and in the second stage reduced search space moving technique is used to minimize the prediction error. The network is trained with fractional frequency change ratios (FFCs) and damage signature indices (DSIs) as effective input patterns and the corresponding damage severity values as output patterns. The patterns are searched at different damage levels by Latin hypercube sampling (LHS) technique. The performance of the novel IRBF method is compared with the conventional RBF and Genetic algorithm (GA) methods and it is found to be a good multiple member damage identification strategy in terms of accuracy and precision with less computational effort.

Sign in / Sign up

Export Citation Format

Share Document