scholarly journals Multidimensional routing with the increased navigation accuracy with the maintenance of flight notifications of the flight vehicles

2021 ◽  
Vol 24 (4) ◽  
pp. 28-37
Author(s):  
V. I. Goncharenko ◽  
G. N. Lebedev ◽  
V. B. Malygin
Keyword(s):  
Genetic Algorithm ◽  
Route Planning ◽  
Optimal Solution ◽  
Weather Conditions ◽  
Flight Vehicles ◽  
General Production ◽  
Dynamic Priorities ◽  
Navigation Accuracy ◽  
The Given ◽  
Weight Coefficients

The article covers the problem the multidimensional routing of flights for the transportation of cargo and mail, with the condition of the corresponding equipment presence for performing navigation of increased precision to obtain the possibility of the formation flights under any weather conditions. The given circumstances are capably essential to reduce load while using the airspace, which will make it possible to achieve transportation independent of its saturation. While planning the routes it is also necessary to consider the interests of different interested groups, which are often opposite to one another. In the view of the different directivity of the tasks in question, the solution can require the sorting as excessively as large, so the smaller quantity of possible situations (versions of the solution), the lower the level of the calculation of these versions is, and the greater their quantity is. The exact example of multidimensional routing, which is affected by the interests of operational nature and the interests of the urgency of the performance of the claims, expressed by weight coefficients, is depicted in this work. The only version in favour of the general production process, which is obtained with the help of a genetic algorithm, is a solution of this problem. It was necessary to introduce some designations and assumptions, the enumeration of which can be supplemented. Optimal solution can be obtained both by the enumeration of the solution versions and with the help of the genetic algorithm, which is allowed for a smaller number of iterations, to obtain suboptimal in real time, which corresponds to the conditions of the task solution. In that the example dynamic priorities are assigned, based on multiplicative form by expert evaluation, which form criteria for the ranking of request for each step of route planning. As a result, there are the exact versions of the solution, which correspond to the interests of different groups and the version, obtained with the help of a genetic algorithm, which satisfy the opposite interests of these groups. All versions of the solution are proved to be different, which indicates the need of applying the objective and substantiated apparatus for making the decision, which the genetic algorithm actually is. The proposed mathematical apparatus has prospects for implementation.

scholarly journals Creating private criteria for A-CDM effectiveness to take into account the interests of decision-making participants in a dynamic environment

2020 ◽  
Vol 23 (6) ◽  
pp. 53-64
Author(s):  
G. N. Lebedev ◽  
V. B. Malygin
Keyword(s):  
Genetic Algorithm ◽  
Decision Making ◽  
Production Process ◽  
Action Plan ◽  
Dynamic Environment ◽  
Weather Conditions ◽  
Collaborative Decision Making ◽  
Emergency Situations ◽  
Dynamic Priorities ◽  
Collaborative Decision

We consider the problem of collaborative decision making of the production process at airlines (CDM) in dynamically changing conditions of occurrence of emergency situations that make changes in the action plan. In the production process, due to the different orientation of the tasks to be solved, the solution may require a large or small number of possible variant solutions. The article presents a concrete example of such a situation affecting the conventional three services of the aviation complex, each with its own interests in the overall production process. The solution to this problem is the only option in favor of the overall production process. For this purpose, several designations and assumptions have been introduced, the list of which can be supplemented. Dynamic priorities are defined for each participant of the process. Optimization of collaborative decision-making can be achieved either by a simple search for solutions, or by using a genetic algorithm that allows you to get a suboptimal solution that meets the requirements of the participants in the process using a smaller number of iterations in real time. In this example, we consider a situation that occurs in a real enterprise due to bad weather conditions. Thus, dynamic priorities are assigned based on a multiplicative form for delayed flights, considering the interests of participants in the process, private criteria are formed for ranking flights at each step of rescheduling, and a genetic algorithm is applied. As a result, we obtained four solutions to the disruption caused by external factors. The first three options correspond to the interests of three parties concerned, and the fourth one is consolidated. All the solutions were different, which indicates the need for an objective and reasonable decision-making apparatus for joint management of the production process. The proposed mathematical apparatus has this ability and prospects for implementation.

Design of 3D-Route Planning Based on the Improvement of Simple Genetic Algorithm

2013 ◽  
Vol 760-762 ◽  
pp. 1690-1694
Author(s):  
Jian Xia Zhang ◽  
Tao Yu ◽  
Ji Ping Chen ◽  
Ying Hao Lin ◽  
Yu Meng Zhang
Keyword(s):  
Genetic Algorithm ◽  
Search Algorithm ◽  
Scientific Research ◽  
Route Planning ◽  
Optimal Solution ◽  
Global Search ◽  
Global Search Algorithm ◽  
Simple Genetic Algorithm ◽  
Local Optimal Solution ◽  
Simulation Results

With the wide application of UAV in the scientific research,its route planning is becoming more and more important. In order to design the best route planning when UAV operates in the field, this paper mainly puts to use the simple genetic algorithm to design 3D-route planning. It primarily introduces the advantages of genetic algorithm compared to others on the designing of route planning. The improvement of simple genetic algorithm is because of the safety of UAV when it flights higher, and the 3D-route planning should include all the corresponding areas. The simulation results show that: the improvement of simple genetic algorithm gets rid of the dependence of parameters, at the same time it is a global search algorithm to avoid falling into the local optimal solution. Whats more, it can meet the requirements of the 3D-route planning design, to the purpose of regional scope and high safety.

scholarly journals Route Planning Based on Genetic Algorithm

2018 ◽  
Vol 10 (2) ◽  
pp. 122 ◽  
Author(s):  
Lin Li ◽  
Yuhua Zhang
Keyword(s):  
Genetic Algorithm ◽  
Fuel Consumption ◽  
Solution Method ◽  
Route Planning ◽  
Optimal Solution ◽  
Initial Population ◽  
Smoothing Algorithm ◽  
Aircraft Fuel ◽  
Consumption Model ◽  
Feasible Solutions

This paper mainly deals with the planning of aviation route and needs to determine the model to find out the shortest path. In this paper, we combine the methods of simulated annealing and genetic algorithm, and obtained the optimal solution method. Firstly, Genetic Algorithm (GA) uses the modified circle algorithm to find some feasible solutions to the approximate initial population, and then transforms them through simulated and crossover operations. This paper also introduces the aircraft fuel consumption model and the cubical smoothing algorithm with five-point approximation to reduce the aircraft fuel consumption and parts loss. The simulation results show that the accuracy of the route planning based on genetic algorithm is higher, while consumes less fuel and takes less sharp turns.

Application of Real-Coded Genetic Algorithm in Ship Weather Routing

2018 ◽  
Vol 71 (4) ◽  
pp. 989-1010 ◽  
Author(s):  
Hong-Bo Wang ◽  
Xiao-Gang Li ◽  
Peng-Fei Li ◽  
Evgeny I. Veremey ◽  
Margarita V. Sotnikova
Keyword(s):  
Genetic Algorithm ◽  
Convergence Rates ◽  
Dynamic Environment ◽  
Route Planning ◽  
Optimal Solution ◽  
Population Diversity ◽  
Assignment Method ◽  
Weather Routing ◽  
Fitness Value ◽  
Real Coded Genetic Algorithm

Solving the problem of ship weather routing has been always a goal of nautical navigation research and has been investigated by many scientists. The operation schedule of an oceangoing ship can be influenced by wave or wind disturbances, which complicate route planning. In this paper, we present a real-coded genetic algorithm to determine the minimum voyage route time for point-to-point problems in a dynamic environment. A fitness assignment method based on an individual's position in the sorted population is presented, which greatly simplifies the calculation of fitness value. A hybrid mutation operator is proposed to enhance the search for the optimal solution and maintain population diversity. Multi-population techniques and an elite retention strategy are employed to increase population diversity and accelerate convergence rates. The effectiveness of the algorithm is demonstrated by numerical simulation experiments.

scholarly journals Multi-Objective Optimization of a Spring Diaphragm Clutch on an Automobile Based on the Non-Dominated Sorting Genetic Algorithm (NSGA-II)

2016 ◽  
Author(s):  
Junchao Zhou ◽  
Chun Wang ◽  
Junjun Zhu
Keyword(s):  
Genetic Algorithm ◽  
Target Function ◽  
Optimal Solution ◽  
Weight Coefficient ◽  
Nsga Ii ◽  
Pressing Force ◽  
Optimization Function ◽  
Separation Force ◽  
Minimum Force ◽  
Weight Coefficients

The weight coefficients of the diaphragm spring depend on experiences in the traditional optimization. However, this method not only cannot guarantee the optimal solution but it is also not universal. Therefore, a new optimization target function is proposed. The new function takes the minimum of average compress force changing of the spring and the minimum force of the separation as total objectives. Based on the optimization function, the result of the clutch diaphragm spring in a car is analyzed by the non-dominated sorting genetic algorithm (NSGA-II) and the solution set of Pareto is obtained. The results show that the pressing force of the diaphragm spring is improved by 4.09%by the new algorithmand the steering separation force is improved by 6.55%, which has better stability and steering portability. The problem of the weight coefficient in the traditional empirical design is solved. The pressing force of the optimized diaphragm spring varied slightly during the abrasion range of the friction film, and the manipulation became remarkably light.

scholarly journals Optimization of Ship Cargo Operations by Genetic Algorithm

2012 ◽  
Vol 21 (4) ◽  
pp. 239-245 ◽  
Author(s):  
Svjetlana Hess ◽  
Mirano Hess
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Optimal Solution ◽  
Mutation Rates ◽  
Acceptable Solution ◽  
Operational Costs ◽  
Decision Variables ◽  
General Cargo ◽  
Short Time ◽  
The Given

This paper addresses the optimization possibilities of cargo operations onboard ship in order to minimize the operational costs through optimal structure of resources required. Since the setup model consists of composite objective function with several decision variables whose solution is constrained in the field Z+, the method for direct finding of optimal solution does not lead to satisfactory results. Therefore, for the solution of the problem a genetic algorithm has been developed, which yields an acceptable solution in a short time. In the given area of the possible solutions, the genetic algorithm, with variations of different crossover methods and mutation rates, gives a solution that coincides with the observed and expected results when operations of loading/unloading of general cargo ship are concerned. With the obtained structure of resources allocated in cargo operations, the minimum of operational costs is reached. KEY WORDS: ship, cargo operations, optimization, genetic algorithm

scholarly journals Inclusion of Hydraulic Controls in Rehabilitation Models of Drainage Networks to Control Floods

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 514
Author(s):  
Leonardo Bayas-Jiménez ◽  
F. Javier Martínez-Solano ◽  
Pedro L. Iglesias-Rey ◽  
Daniel Mora-Melia ◽  
Vicente S. Fuertes-Miquel
Keyword(s):  
Genetic Algorithm ◽  
Drainage System ◽  
Optimal Solution ◽  
Hydraulic Control ◽  
Drainage Systems ◽  
Storm Water Management Model ◽  
Drainage Networks ◽  
Extreme Rain ◽  
Rain Events ◽  
The Cost

A problem for drainage systems managers is the increase in extreme rain events that are increasing in various parts of the world. Their occurrence produces hydraulic overload in the drainage system and consequently floods. Adapting the existing infrastructure to be able to receive extreme rains without generating consequences for cities’ inhabitants has become a necessity. This research shows a new way to improve drainage systems with minimal investment costs, using for this purpose a novel methodology that considers the inclusion of hydraulic control elements in the network, the installation of storm tanks and the replacement of pipes. The presented methodology uses the Storm Water Management Model for the hydraulic analysis of the network and a modified Genetic Algorithm to optimize the network. In this algorithm, called the Pseudo-Genetic Algorithm, the coding of the chromosomes is integral and has been used in previous studies of hydraulic optimization. This work evaluates the cost of the required infrastructure and the damage caused by floods to find the optimal solution. The main conclusion of this study is that the inclusion of hydraulic controls can reduce the cost of network rehabilitation and decrease flood levels.

scholarly journals Business E-NeGotiAtion: A Method Using a Genetic Algorithm for Online Dispute Resolution in B2B Relationships

2021 ◽  
Vol 16 (5) ◽  
pp. 1186-1216
Author(s):  
Nikola Simkova ◽  
Zdenek Smutny
Keyword(s):  
Genetic Algorithm ◽  
Dispute Resolution ◽  
Single Case ◽  
Computer Mediated Communication ◽  
Optimal Solution ◽  
Mediated Communication ◽  
Online Dispute Resolution ◽  
B2b Relationships ◽  
Definition Of ◽  
E Mail

An opportunity to resolve disputes as an out-of-court settlement through computer-mediated communication is usually easier, faster, and cheaper than filing an action in court. Artificial intelligence and law (AI & Law) research has gained importance in this area. The article presents a design of the E-NeGotiAtion method for assisted negotiation in business to business (B2B) relationships, which uses a genetic algorithm for selecting the most appropriate solution(s). The aim of the article is to present how the method is designed and contribute to knowledge on online dispute resolution (ODR) with a focus on B2B relationships. The evaluation of the method consisted of an embedded single-case study, where participants from two countries simulated the realities of negotiation between companies. For comparison, traditional negotiation via e-mail was also conducted. The evaluation confirms that the proposed E-NeGotiAtion method quickly achieves solution(s), approaching the optimal solution on which both sides can decide, and also very importantly, confirms that the method facilitates negotiation with the partner and creates a trusted result. The evaluation demonstrates that the proposed method is economically efficient for parties of the dispute compared to negotiation via e-mail. For a more complicated task with five or more products, the E-NeGotiAtion method is significantly more suitable than negotiation via e-mail for achieving a resolution that favors one side or the other as little as possible. In conclusion, it can be said that the proposed method fulfills the definition of the dual-task of ODR—it resolves disputes and builds confidence.

Commercial Vehicle Route Planning Design Based on Partition Coding Genetic Algorithm

2020 ◽  
Author(s):  
Kailang Chen ◽  
Hanyu Zhang ◽  
Xin Huang ◽  
Long Chen ◽  
Qi Shi
Keyword(s):  
Genetic Algorithm ◽  
Commercial Vehicle ◽  
Route Planning ◽  
Vehicle Route
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