scholarly journals Optimization of Energetic Train Cooperation

Symmetry ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1175 ◽  
Author(s):  
Urbaniak ◽  
Kardas-Cinal ◽  
Jacyna
Keyword(s):  
Firefly Algorithm ◽  
Arrival Time ◽  
Optimization Method ◽  
Original Model ◽  
Regenerative Braking ◽  
Conservation Of Energy ◽  
Energy Cooperation ◽  
Railway Line ◽  
Double Track ◽  
Time Reserve

In the article, possible ways of using energy recovered during regenerative braking of trains are presented. It is pointed out that the return of recovered electricity directly to the catenary and its use in the energy cooperation of vehicles can be a no-cost method (without additional infrastructure). The method of energy cooperation between trains and its main assumptions, that uses the law of conservation of energy, are described in detail. An original model is proposed which assumes optimization by controlling the train arrival time at the station within the technical time reserve. Optimization method was used metaheuristic and adapted swarm algorithm called the firefly algorithm. An exemplary simulation of the energy cooperation of trains for selected stops of a double-track railway line of the Tricity Rapid Urban Railway has been done and the obtained results are presented. Finally, in discussion and conclusions, the results were summarized and the significance of the development of the discussed method for transport rationalization was presented.

scholarly journals Operational criteria in the justification of electrification of railway lines

2018 ◽  
Vol 180 ◽  
pp. 06005
Author(s):  
Andrzej Massel
Keyword(s):  
Rolling Stock ◽  
The Political ◽  
Economic Factors ◽  
Single Track ◽  
Railway Network ◽  
Railway Line ◽  
Passenger Traffic ◽  
Post War ◽  
Operational Criteria ◽  
Double Track

The process of electrification of the Polish railways took place from 1936 till early 1990s. Despite the political constraints of the post-war times, the decisions on electrification of particular sections of the railway network were usually based on economic factors. In 1970s and 1980s so called electrification thresholds were used to justify the need for electrification of railway line in question. They took into the number of tracks (single-track lines, double-track lines), terrain conditions (flat terrain, upland terrain) and the traffic structure (the share of passenger traffic) into account. In the framework of National Railway Program till 2023 (KPK) the realization of electrification projects have been undertaken again. The present paper deals with importance of the operational criteria in the decision-making concerning justification of electrification of railway lines. These criteria include the shortening of the journey times on particular sections, shortening of stops on the stations with the change of the type of traction, the savings of train operating companies resulting from the traction unification (change of demand for rolling stock and for workshops for its servicing), improvement of reliability and punctuality of services.

scholarly journals Delay Bound Optimization in NoC Using a Discrete Firefly Algorithm

Electronics ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 1507
Author(s):  
Gaoming Du ◽  
Chao Tian ◽  
Zhenmin Li ◽  
Duoli Zhang ◽  
Chuan Zhang ◽  
...  
Keyword(s):  
Firefly Algorithm ◽  
Optimization Method ◽  
Video Object ◽  
Worst Case ◽  
Delay Bound ◽  
Proposed Model ◽  
Discrete Firefly Algorithm ◽  
Firefly Optimization ◽  
On Chip ◽  
Bound Optimization

The delay bound in system on chips (SoC) represents the worst-case traverse time of on-chip communication. In network on chip (NoC)-based SoC, optimizing the delay bound is challenging due to two aspects: (1) the delay bound is hard to obtain by traditional methods such as simulation; (2) the delay bound changes with the different application mappings. In this paper, we propose a delay bound optimization method using discrete firefly optimization algorithms (DBFA). First, we present a formal analytical delay bound model based on network calculus for both unipath and multipath routing in NoCs. We then set every flow in the application as the target flow and calculate the delay bound using the proposed model. Finally, we adopt firefly algorithm (FA) as the optimization method for minimizing the delay bound. We used industry patterns (video object plane decoder (VOPD), multiwindow display (MWD), etc.) to verify the effectiveness of delay bound optimization method. Experiments show that the proposed method is both effective and reliable, with a maximum optimization of 42.86%.

scholarly journals Size and Topology Optimization for Trusses with Discrete Design Variables by Improved Firefly Algorithm

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Yue Wu ◽  
Qingpeng Li ◽  
Qingjie Hu ◽  
Andrew Borgart
Keyword(s):  
Topology Optimization ◽  
Firefly Algorithm ◽  
Optimization Problems ◽  
Optimization Method ◽  
Structural Topology ◽  
Discrete Variables ◽  
And Topology ◽  
Design Variables ◽  
Improved Firefly Algorithm ◽  
Discrete Design Variables

Firefly Algorithm (FA, for short) is inspired by the social behavior of fireflies and their phenomenon of bioluminescent communication. Based on the fundamentals of FA, two improved strategies are proposed to conduct size and topology optimization for trusses with discrete design variables. Firstly, development of structural topology optimization method and the basic principle of standard FA are introduced in detail. Then, in order to apply the algorithm to optimization problems with discrete variables, the initial positions of fireflies and the position updating formula are discretized. By embedding the random-weight and enhancing the attractiveness, the performance of this algorithm is improved, and thus an Improved Firefly Algorithm (IFA, for short) is proposed. Furthermore, using size variables which are capable of including topology variables and size and topology optimization for trusses with discrete variables is formulated based on the Ground Structure Approach. The essential techniques of variable elastic modulus technology and geometric construction analysis are applied in the structural analysis process. Subsequently, an optimization method for the size and topological design of trusses based on the IFA is introduced. Finally, two numerical examples are shown to verify the feasibility and efficiency of the proposed method by comparing with different deterministic methods.

scholarly journals Railway Planning Double-Double Track (Case Study of Bekasi Station km 26 + 652 - Jatinegara Station km 12 + 050

2020 ◽  
Vol 4 (1) ◽  
pp. 12-21
Author(s):  
Ido Prasetio ◽  
Andri Irfan Rifai
Keyword(s):  
Human Error ◽  
Urban Land Use ◽  
Single Track ◽  
Train Track ◽  
Railway Line ◽  
Railway Planning ◽  
Physical Changes ◽  
Double Track ◽  
The Impact

Increasing the number of population and the development of activities will cause a growing need for space every day, this will result in physical changes and urban land use and can cause increased intensity of population movement from Megapolitan cities such as Bekasi, Bogor and Tangerang to the Metropolitan city (DKI Jakarta). Some people have now started to move from private vehicles to use public (mass) transportation such as buses, transjakarta, and electric rail trains or commonly known as KRL Commuter Line that serve Jabodetabek routes. The impact of crossing also causes buildup at each station. Train track with a single track (single track) is considered ineffective and inefficient and vulnerable to train accidents due to human error. It is necessary to develop or develop a double track to become a double-double track Bekasi Station km 26 + 652 - Jatinegara Station km 12 + 050. The research location is on the railway line from Bekasi Station to Jatinegara Station. The length of the train track is around 16 km and has 7 stations that are traversed, 5 of which are active (stop) and 2 passive stations.

scholarly journals The architecture of decision-making support systems used for the rational railway capacity management

2021 ◽  
Author(s):  
Ivica Ljubaj ◽  
Tomislav Josip Mlinarić ◽  
Slavko Vesković ◽  
Dušan Jeremić
Keyword(s):  
Decision Making ◽  
Support System ◽  
Traffic Control ◽  
Support Systems ◽  
Specific Model ◽  
Railway Transport ◽  
Railway Line ◽  
Railway Capacity ◽  
Double Track ◽  
Decision Making Support

Decision-making support systems in railway transport are systems that make it easier for traffic controllers and dispatchers involved in the regulation of train traffic to make individual decisions more easily and accurately. Without such systems, dispatchers usually make decisions based on previous experiences and feelings they have developed working in train traffic control. However, quality decision-making support systems are based on large amounts of data processed by one or several different artificial intelligence techniques. This paper will examine the architecture of such a system in railway transport, which helps the dispatcher to make decisions based on different criteria and values of individual criteria. The architecture of this decision-making support system has been developed to equal or, if necessary, use the maximum available double-track railway line capacity to resolve delays caused by lack of capacity for any given route. This system has been developed for the specific configuration of a double track, whereby each track is intended for one direction of train traffic. This paper will lay the foundation for understanding decision-making support systems and for the development of a specific model of decision-making support system in practice.

Structural Parameters Optimization of Excavator Working Device Based on Mining Process

2011 ◽  
Vol 421 ◽  
pp. 759-763 ◽  
Author(s):  
Tian Zhong Sui ◽  
Lei Wang ◽  
Zhen Tan ◽  
Pei Chao Jia
Keyword(s):  
System Theory ◽  
Structural Parameters ◽  
Optimization Method ◽  
Original Model ◽  
Parameters Optimization ◽  
Structure Parameter ◽  
Multi Objective Optimization ◽  
Complex Optimization ◽  
The Mind ◽  
Working Device

With a view to the whole digging process, a multi-objective optimization model based on digging process is established. Applying the mind of system theory and complex optimization method, taking model P&H2800XP excavator for example, the structure parameter optimization of its working device is accomplished. The rational parameters obtained from this. Comparing with an original model, optimized results are ideal comparatively and the performance is improved.

scholarly journals Simulating the Effects of Noncrossing Block Sections Setting Rules on Capacity Loss of Double-Track Railway Line due to the Operation of out-of-Gauge Trains

2016 ◽  
Vol 2016 ◽  
pp. 1-16 ◽  
Author(s):  
Yinggui Zhang ◽  
Qiong-fang Zeng ◽  
Dingyou Lei ◽  
Xinyu Wang
Keyword(s):  
Assessment Model ◽  
Simulation Experiments ◽  
Railway Line ◽  
Capacity Loss ◽  
Operation Rules ◽  
Upstream Direction ◽  
Optimal Setting ◽  
Railway Capacity ◽  
Set Up ◽  
Double Track

Dispatchers often set noncrossing block sections (NCBSs) for railway out-of-gauge train (OGT) running on double-track railway line for safety reasons. In this paper, we will investigate the best location, length, and number of noncrossing block sections to reduce railway capacity loss due to the operation of OGTs. Firstly, yielding, overtaking, stopping, starting, and other operation rules for OGTs running on double-track railway line were designed, and a simulation model based on cellular automata was further put forward. Then, an assessment model for double-track railway line capacity loss due to the operation of OGTs was set up. Some simulation experiments and the comparisons of these results were further given to achieve the optimal setting of NCBS for OGTs running on double-track railway line. In the case of NCBSs number minus one, capacity loss caused by the operation of OGTs can be reduced up to 15.2% in the upstream direction and 6.3% in the downstream direction. Also, the NCBSs should lie at the nearest block sections (BSs) to depot stations and the NCBSs lengths should be as less as possible.

scholarly journals Aplikasi Hybrid Firefly Algorithm untuk Pemecahan Masalah Traveling Salesman: Studi Kasus pada PT Anugerah Mandiri Success

2014 ◽  
Vol 5 (2) ◽  
pp. 828
Author(s):  
J. Sudirwan ◽  
Siti Nur Fadlilah ◽  
Teguh Teguh
Keyword(s):  
Fuel Consumption ◽  
Firefly Algorithm ◽  
Nearest Neighbor ◽  
Heuristic Method ◽  
Optimization Method ◽  
Traveling Salesman ◽  
Total Distance ◽  
Metaheuristic Methods ◽  
Hybrid Firefly Algorithm

Determining a good route is a major problem in a transport process in the company. This case study aims to overcome the problem of determining the route or often called the Traveling Salesman Problem (TSP) is optimal. This problem will be solved by the optimization method in determining the route, which is more systematic in PT Anugerah Mandiri Success. Metaheuristic methods, such as Hybrid Firefly Algorithm is used to assist the system in the process of determining the route. Hybrid Firefly Algorithm combines heuristic method of Nearest Neighbor Heuristic with metaheuristic method of Levy Flight Discrete Firefly Algorithm. The indicators used in this case study are the total distance traveled and total fuel used. Methods Object Oriented Analysis andDesign (OOAD) is used to develop an information system, which consists of determining system requirements, system architecture design, and design to the trials of the system were developed. The results of the constructedsystem provide a solution in the form of route determination with a total distance of 165.1 kilometers with a fuel consumption of 11,793 liters. These results are much better when compared with historical data that has a totaldistance of 260.8 kilometers with a fuel consumption of 18,628 liters.

scholarly journals Gender-Based Deep Learning Firefly Optimization Method for Test Data Generation

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Wenning Zhang ◽  
Chongyang Jiao ◽  
Qinglei Zhou ◽  
Yang Liu ◽  
Ting Xu
Keyword(s):  
Deep Learning ◽  
Test Data ◽  
Firefly Algorithm ◽  
Optimization Problems ◽  
Optimization Method ◽  
Test Data Generation ◽  
Data Generation ◽  
Whole Space ◽  
Automatic Test Data Generation ◽  
Gender Based

Software testing is a widespread validation means of software quality assurance in industry. Intelligent optimization algorithms have been proved to be an effective way of automatic test data generation. Firefly algorithm has received extensive attention and been widely used to solve optimization problems because of less parameters and simple implement. To overcome slow convergence rate and low accuracy of the firefly algorithm, a novel firefly algorithm with deep learning is proposed to generate structural test data. Initially, the population is divided into male subgroup and female subgroup. Following the randomly attracted model, each male firefly will be attracted by another randomly selected female firefly to focus on global search in whole space. Each female firefly implements local search under the leadership of the general center firefly, constructed based on historical experience with deep learning. At the final period of searching, chaos search is conducted near the best firefly to improve search accuracy. Simulation results show that the proposed algorithm can achieve better performance in terms of success coverage rate, coverage time, and diversity of solutions.

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