scholarly journals MODEL OF WORKING SHIP CROSSING CHANNEL

Brodogradnja ◽  
2021 ◽  
Vol 72 (1) ◽  
pp. 125-143
Author(s):  
Zhang He ◽  
◽  
Hao Yuanyuan ◽  
Xu Cheng ◽  
Qin Luying
Keyword(s):  
Genetic Algorithm ◽  
Genetic Factors ◽  
Measured Data ◽  
Decision Makers ◽  
Time Range ◽  
Safe Distance ◽  
Hydrological Conditions ◽  
Starting Time ◽  
Ship Navigation ◽  
Navigation Scheme

An application method for working ship crossing safely is proposed to determine how to make navigation scheme at a certain time. This method makes it possible for decision makers to make reasonable judgments at different times. In this paper, the position relationship between working ship and navigation vessel in waterway is analysed by considering the ship size, hydrological conditions of waterway, ship arrival model and ship navigation trajectory. Using genetic algorithm, the operation scheme of keeping a safe distance between the working ship and the vessel in the channel is solved by taking the speed and direction of the working ship as genetic factors. By analysing the crossing scheme at each starting time in a given time range, the optimal crossing scheme with the farthest distance between the working ship and the vessels in the channel is obtained. According to the measured data, the simulation is carried out with MATLAB to verify the model of working ship crossing channel. The results show that it is safe and reliable to choose the navigation scheme proposed in this paper, which has strong application value.

scholarly journals Research on Intelligent Avoidance Method of Shipwreck Based on Bigdata Analysis

2017 ◽  
Vol 24 (s3) ◽  
pp. 213-220 ◽  
Author(s):  
Wei Li ◽  
Qian Huang
Keyword(s):  
Genetic Algorithm ◽  
Big Data ◽  
Data Analysis ◽  
Success Rate ◽  
Traditional Method ◽  
Big Data Analysis ◽  
Evaluation Function ◽  
Safe Distance ◽  
Recent Meeting ◽  
Ship Navigation

Abstract In order to solve the problem that current avoidance method of shipwreck has the problem of low success rate of avoidance, this paper proposes a method of intelligent avoidance of shipwreck based on big data analysis. Firstly,our method used big data analysis to calculate the safe distance of approach of ship under the head-on situation, the crossing situation and the overtaking situation.On this basis, by calculating the risk-degree of collision of ships,our research determined the degree of immediate danger of ships.Finally, we calculated the three kinds of evaluation function of ship navigation, and used genetic algorithm to realize the intelligent avoidance of shipwreck.Experimental result shows that compared the proposed method with the traditional method in two in a recent meeting when the distance to closest point of approach between two ships is 0.13nmile, they can effectively evade.The success rate of avoidance is high.

scholarly journals A Method for Integration of Preferences to a Multi-Objective Evolutionary Algorithm Using Ordinal Multi-Criteria Classification

2021 ◽  
Vol 26 (2) ◽  
pp. 27
Author(s):  
Alejandro Castellanos-Alvarez ◽  
Laura Cruz-Reyes ◽  
Eduardo Fernandez ◽  
Nelson Rangel-Valdez ◽  
Claudia Gómez-Santillán ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Selective Pressure ◽  
Optimization Problems ◽  
Region Of Interest ◽  
Decision Makers ◽  
Multiple Objective ◽  
Objective Functions ◽  
Multi Objective ◽  
Imperfect Knowledge ◽  
Real World Problems

Most real-world problems require the optimization of multiple objective functions simultaneously, which can conflict with each other. The environment of these problems usually involves imprecise information derived from inaccurate measurements or the variability in decision-makers’ (DMs’) judgments and beliefs, which can lead to unsatisfactory solutions. The imperfect knowledge can be present either in objective functions, restrictions, or decision-maker’s preferences. These optimization problems have been solved using various techniques such as multi-objective evolutionary algorithms (MOEAs). This paper proposes a new MOEA called NSGA-III-P (non-nominated sorting genetic algorithm III with preferences). The main characteristic of NSGA-III-P is an ordinal multi-criteria classification method for preference integration to guide the algorithm to the region of interest given by the decision-maker’s preferences. Besides, the use of interval analysis allows the expression of preferences with imprecision. The experiments contrasted several versions of the proposed method with the original NSGA-III to analyze different selective pressure induced by the DM’s preferences. In these experiments, the algorithms solved three-objectives instances of the DTLZ problem. The obtained results showed a better approximation to the region of interest for a DM when its preferences are considered.

scholarly journals Optimization of Vehicle-to-Vehicle Frontal Crash Model Based on Measured Data Using Genetic Algorithm

IEEE Access ◽  
2017 ◽  
Vol 5 ◽  
pp. 3131-3138 ◽  
Author(s):  
Bernard B. Munyazikwiye ◽  
Hamid Reza Karimi ◽  
Kjell G. Robbersmyr
Keyword(s):  
Genetic Algorithm ◽  
Measured Data ◽  
Frontal Crash ◽  
Model Based ◽  
Vehicle To Vehicle ◽  
Crash Model

scholarly journals Genetic Algorithm for Optimizing Routing Design and Fleet Allocation of Freeway Service Overlapping Patrol

2018 ◽  
Vol 10 (11) ◽  
pp. 4120 ◽  
Author(s):  
Xiuqiao Sun ◽  
Jian Wang ◽  
Weitiao Wu ◽  
Wenjia Liu
Keyword(s):  
Genetic Algorithm ◽  
Population Diversity ◽  
Decision Makers ◽  
Incident Response ◽  
Matrix Encoding ◽  
Routing Design ◽  
Speed Up ◽  
Fleet Allocation ◽  
Patrol Routing ◽  
Elitist Strategy

The freeway service patrol problem involves patrol routing design and fleet allocation on freeways that would help transportation agency decision-makers when developing a freeway service patrols program and/or altering existing route coverage and fleet allocation. Based on the actual patrol process, our model presents an overlapping patrol model and addresses patrol routing design and fleet allocation in a single integrated model. The objective is to minimize the overall average incident response time. Two strategies—overlapping patrol and non-overlapping patrol—are compared in our paper. Matrix encoding is applied in the genetic algorithm (GA), and to maintain population diversity and avoid premature convergence, a niche strategy is incorporated into the traditional genetic algorithm. Meanwhile, an elitist strategy is employed to speed up the convergence. Using numerical experiments conducted based on data from the Sioux Falls network, we clearly show that: overlapping patrol strategy is superior to non-overlapping patrol strategy; the GA outperforms the simulated annealing (SA) algorithm; and the computational efficiency can be improved when LINGO software is used to solve the problem of fleet allocation.

scholarly journals Genetic Algorithm Based Solution of Fuzzy Multi-Objective Transportation Problem

2020 ◽  
Vol 5 (6) ◽  
pp. 1452-1467
Author(s):  
Jaydeepkumar M. Sosa ◽  
Jayesh M. Dhodiya
Keyword(s):  
Genetic Algorithm ◽  
Transportation Problem ◽  
Shape Parameter ◽  
Optimization Problems ◽  
Decision Makers ◽  
Objective Functions ◽  
Full Data ◽  
Multi Objective ◽  
Life Problems ◽  
Modern Era

Optimizing problems in the modern era, the single objective optimization problems are insufficient to hold the full data of the problem. Therefore, multi-objective optimization problems come to the rescue. Similarly, in daily life problems, the parameters used in the optimization problem are not always fixed but there may be some uncertainty and it can characterize by fuzzy number. This work underlines the genetic algorithm (GA) based solution of fuzzy transportation problem with more than one objective. With a view to providing the multifaceted choices to decision-maker (DM), the exponential membership function is used with the decision-makers desired number of cases which consisted of shape parameter and aspiration level. Here, we consider the objective functions which are non-commensurable and conflict with each other. To interpret, evaluate and exhibit the usefulness of the proposed method, a numerical example is given.

scholarly journals Weather-Routing System Based on METOC Navigation Risk Assessment

2019 ◽  
Vol 7 (5) ◽  
pp. 127 ◽  
Author(s):  
Tommaso Fabbri ◽  
Raul Vicen-Bueno
Keyword(s):  
Risk Assessment ◽  
Decision Makers ◽  
The Other ◽  
Added Resistance ◽  
Minimum Risk ◽  
Weather Routing ◽  
Risk Criterion ◽  
Ship Navigation ◽  
Alternative Routes ◽  
Safety Guidelines

This paper presents a novel weather-routing system based on a multi-criteria setup. The set of 3 conflicting criteria is: travel time, ship navigation added resistance (caused by wind and waves), and navigation risk/safety. To this aim, the International Maritime Organization (IMO) safety guidelines are exploited for the design of navigation risk criterion as a function of the METeorological and OCeanographic (METOC) and sailing conditions. This risk is directly integrated into the multi-criteria setup, as an innovative alternative to the systems proposed in the open literature. The proposed methodology is tested in a real operational scenario in the Mediterranean Sea. The obtained results show how the proposed system provides alternative routes with minimum risk to the decision-makers, as well as other different alternative routes minimizing the other criteria.

scholarly journals Goal-Programming-Driven Genetic Algorithm Model for Wireless Access Point Deployment Optimization

2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
Chen-Shu Wang ◽  
Ching-Ter Chang
Keyword(s):  
Genetic Algorithm ◽  
Goal Programming ◽  
Access Point ◽  
Wireless Networking ◽  
Complex Problem ◽  
Decision Makers ◽  
Wireless Access ◽  
Optimal Deployment ◽  
Capacity Loading ◽  
Wireless Access Point

Appropriate wireless access point deployment (APD) is essential for ensuring seamless user communication. Optimal APD enables good telecommunication quality, balanced capacity loading, and optimal deployment costs. APD is a typical NP-complex problem because improving wireless networking infrastructure has multiple objectives (MOs). This paper proposes a method that integrates a goal-programming-driven model (PM) and a genetic algorithm (GA) to resolve the MO-APD problem. The PM identifies the target deployment subject of four constraints: budget, coverage, capacity, and interference. The PM also calculates dynamic capacity requirements to replicate real wireless communication. Three experiments validate the feasibility of the PM. The results demonstrate the utility and stability of the proposed method. Decision makers can easily refer to the PM-identified target deployment before allocating APs.

Hydro Turbine Nonlinear Model Parameter Identification Based on Improved Biogeography-Based Optimization

2014 ◽  
Vol 672-674 ◽  
pp. 1617-1621
Author(s):  
Jie Zhao ◽  
Li Wang ◽  
Yu Heng Tang ◽  
Di Chen Liu ◽  
Wen Tao Sun
Keyword(s):  
Genetic Algorithm ◽  
Nonlinear Model ◽  
Measured Data ◽  
Operating Efficiency ◽  
Swarm Optimization ◽  
Identification Methods ◽  
Species Migration ◽  
Hydro Turbine ◽  
Data Comparison ◽  
Improve Operating

The nonlinear model of hydro turbine considering the elastic water column was proposed, and the improved biogeography-based optimization (IBBO) algorithm was applied to identify parameters of this model. The cosine species migration model and the elitist reservation strategy were introduced into the algorithm to improve operating efficiency. Based on measured data, comparison of the effects of different identification methods was presented, including the IBBO algorithm, genetic algorithm (GA) and particle swarm optimization (PSO). The results demonstrated that the IBBO algorithm can be applied in parameters identification of hydro turbine nonlinear model, and it has the advantages of faster convergence and higher precision.

A New Form of Genetic Algorithm for Back-Calculating Pavement Structure Modulus Based on Database Searching Theory

2012 ◽  
Vol 193-194 ◽  
pp. 1090-1094
Author(s):  
Xin Jian Feng ◽  
Jian Fang Fu ◽  
Jian Lin Zhang
Keyword(s):  
Genetic Algorithm ◽  
Traditional Method ◽  
Measured Data ◽  
Database Searching ◽  
Falling Weight Deflectometer ◽  
Load Pulse ◽  
New Form ◽  
Pavement Structure ◽  
Falling Weight ◽  
Better Than

The Falling Weight Deflectometer (FWD) is designed to impart a load pulse to the pavement surface which simulates the load produced by a rolling vehicle wheel, wildly used in back-calculating pavement structure modulus. In this paper, a new form of Genetic Algorithm based on database searching theory is introduced. This method is not sensitive to initial values and it could identify the modulus effectively with establishing simple databases. By using a project measured data as an example, the result shows that this method is stable, convergent and practical. This method is better than the traditional method. It will be one of useful tools for the highway assessment.

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