Route Planning of Helicopters Spraying Operations in Multiple Forest Areas

It is of great value to research the problem of forest pest and disease control. Currently, helicopters play an important role in dealing with this problem. However, the spraying route planning still depends on the pilot’s driving experience, which leads to low efficiency and less accurate coverage. For this reason, this paper attempts to use intelligent algorithms to plan the pesticide spraying route for helicopters. When the helicopter is conducting spraying operations in multiple forest areas, the routes are divided into two parts: pesticide spraying routes for individual forest areas and dispatch routes between multiple forest areas. First, the shorter spraying route with fewer turnarounds for individual forest areas was determined. Then a two-layer intelligent algorithm, a combination of a genetic algorithm (GA) and ant colony optimization algorithm (ACO), was designed to determine the dispatch route between multiple forest areas, which is referred to as GAACO-GA. The performance was evaluated in self-created multiple forest areas and compared with other two-layer intelligent algorithms. The results show that the GAACO-GA algorithm found the shortest dispatch route (5032.75 m), which was 5.60%, 5.45%, 6.54%, and 4.07% shorter than that of GA-GA algorithm, simulated annealing-GA (SA-GA) algorithm, ACO-GA algorithm, and particle swarm optimization-GA (PSO-GA) algorithm, respectively. A spraying experiment with a helicopter was conducted near Pigzui Mountain, Huai’an City, Jiangsu Province, China. It was found that the flight path obtained from the proposed algorithm was 5.43% shorter than that derived from a manual planning method. The dispatch route length was reduced by 16.93%, the number of turnarounds was reduced by 11 times, and the redundant coverage was reduced by 17.87%. Moreover, helicopter fuel consumption and pesticide consumption decreased by 10.56% and 5.43%, respectively. The proposed algorithm can shorten the application route, reduce the number of turnarounds and the cost of spraying operations, and has the potential for use in spraying operations in smart forestry and agriculture.

Download Full-text

Calculate Accurate 3D Cost Distance Efficiently

Abstracts of the ICA ◽

10.5194/ica-abs-1-42-2019 ◽

2019 ◽

Vol 1 ◽

pp. 1-1

Author(s):

Yaqian Chen ◽

Jiangfeng She ◽

Xingong Li

Keyword(s):

Data Structure ◽

Distance Function ◽

Friction Surface ◽

Hash Table ◽

Route Planning ◽

Weighted Interpolation ◽

Cost Distance ◽

Distance Weighted ◽

Cost Paths ◽

The Cost

Abstract. Cost distance is one of the fundamental functions in geographic information systems (GIS), which has been used in various applications such as route planning, construction of Thiessen polygons and distance weighted interpolation. Conventional 2D cost distance function, due to its limited movement directions (either 4 or 8 neighbourhood cells) in the raster data model, overestimates the least cost and the problem is especially severe with a homogeneous friction surface. 3D cost distance function removes the limitation that movement must occur on a planar surface. It can therefore take into account tunnels and bridges when calculating least cost paths. In addition, it can also be used in many other application domains which deal with 3D geospatial data such as in atmospheric science, geology, and oceanography. Based on the method in Tomlin (2010), which can completely eliminate the overestimation when traveling on a homogeneous friction surface, this research proposes an algorithm that calculates accurate least cost with both homogeneous and heterogeneous friction in 3D space. When extending the cost distance function from 2D to 3D, the number of voxels in the propagation front increases significantly and efficiency is an imperative issue. This research also improves the computational efficiency by developing a data structure that combines a binary heap and a hash table. Our results show that the proposed algorithm can calculate accurate 3D cost distance in a homogeneous friction space, and the proposed data structure (i.e., heap plus hash table) not only significantly reduces the algorithm’s runtime but also benefits more in 3D than in 2D. In addition, we have applied the method in a 3D drone delivery routing application in a city environment (Figure 1). Additional applications, such as calculating groundwater flow paths of least hydraulic resistance in a heterogeneous 3D hydraulic conductivity field, are currently under development.

Download Full-text

Route Planning: B

Probability in Electrical Engineering and Computer Science ◽

10.1007/978-3-030-49995-2_14 ◽

2021 ◽

pp. 259-269

Author(s):

Jean Walrand

Keyword(s):

Route Planning ◽

The State ◽

Control Problems ◽

Linear Quadratic ◽

Linear Quadratic Gaussian ◽

Certainty Equivalence ◽

Markov Decision Problems ◽

Markov Decision ◽

The Cost ◽

Elegant Solution

AbstractThere is a class of control problems that admit a particularly elegant solution: the linear quadratic Gaussian (LQG) problems. In these problems, the state dynamics and observations are linear, the cost is quadratic, and the noise is Gaussian. Section 14.1 explains the theory of LQG problems when one observes the state. Section 14.2 discusses the situation when the observations are noisy and shows the remarkable certainty equivalence property of the solution. Section 14.3 explains how noisy observations affect Markov decision problems.

Download Full-text

Routing Optimization of High-Level Order Picking Truck Based on Swarm Intelligent Algorithm

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.101-102.414 ◽

2011 ◽

Vol 101-102 ◽

pp. 414-417

Author(s):

Yi Qiang Wang ◽

Chao Fu ◽

Ming Yang Ma ◽

Lin Bin Wang

Keyword(s):

Optimization Problem ◽

Order Picking ◽

Intelligent Algorithm ◽

Swarm Optimization ◽

Intelligent Algorithms ◽

Operation Efficiency ◽

Routing Optimization ◽

High Level ◽

The Mathematical Model ◽

Level Order

In order to improve the operation efficiency of order picking trucks in the warehouse, the mathematical model of the routing optimization problem is established. Then PSO (Particle Swarm Optimization) and ACO (Ant Colony Optimization) are used to solve the model. Experimental results show that both of them have good overall search ability and astringency. The operation efficiency is improved to a great extent by using swarm intelligent algorithms.

Download Full-text

ROUTE PLANNING BASED ON UNCERTAIN INFORMATION IN TRANSPORT NETWORKS

Transport ◽

10.3846/16484142.2012.667835 ◽

2012 ◽

Vol 27 (1) ◽

pp. 79-85 ◽

Cited By ~ 2

Author(s):

Gábor Szűcs

Keyword(s):

Traffic Congestion ◽

Traffic Accidents ◽

Decision Rules ◽

Route Planning ◽

Transport Network ◽

Uncertain Information ◽

End User ◽

Dempster Shafer Theory ◽

Shafer Theory ◽

The Cost

The goal of this paper is to find a solution for route planning in a transport network where the network type can be arbitrary: a network of bus routes, a network of tram rails, a road network or any other type of a transport network. Furthermore, the costs of network elements are uncertain. The concept is based on the Dempster–Shafer theory and Dijkstra's algorithm which helps with finding the best routes. The paper focuses on conventional studies without considering traffic accidents or other exceptional circumstances. The concept is presented by an undirected graph. In order to model conventional real transport, the influencing factors of traffic congestion have been applied in the abstract model using uncertain probabilities described by probability intervals. On the basis of these intervals, the cost intervals of each road can be calculated. Taking into account the uncertain values of costs, an algorithm has been outlined for determining the best routes from one node to all other nodes comparing cost intervals and using decision rules that can be defined by the end user, and if necessary, node by node. The suggested solution can be applied for both one type of network as well as for a combination of a few of those.

Download Full-text

Application of Logistical Balancing Method in Manufacturing and Assembly Line

Materials Science Forum ◽

10.4028/www.scientific.net/msf.626-627.699 ◽

2009 ◽

Vol 626-627 ◽

pp. 699-704

Author(s):

Yuan Zhang

Keyword(s):

Assembly Line ◽

Small And Medium Enterprises ◽

Program Cost ◽

Iterative Computation ◽

Low Efficiency ◽

Medium Enterprises ◽

The Cost ◽

Short Time ◽

The Way

In view of low efficiency and high cost during the operation of the manufacturing and assembly line to redistribute workpieces, this paper presents a logistical balancing method based on time and costs in manufacturing and assembly line. The workpieces are selected in a short time by use of database and spreadsheet. The iterative computation will stop when the expense is higher than benefit. This method is especially suitable for the small and medium enterprises which can not burden the re-program cost. An example about Harbin HBC Value Co. Ltd is given to explain the logistical balancing method. The results show that the implementation of this logistics balancing method offer the way to improve the efficiency of vacant time by 62.6% and the cost of product is reduced greatly.

Download Full-text

Minimizing the Impact of Large Freight Vehicles in the City: A Multicriteria Vision for Route Planning and Type of Vehicles

Journal of Advanced Transportation ◽

10.1155/2018/1732091 ◽

2018 ◽

Vol 2018 ◽

pp. 1-8 ◽

Cited By ~ 2

Author(s):

Sara Ezquerro ◽

Juan P. Romero ◽

Jose L. Moura ◽

Juan Benavente ◽

Ángel Ibeas

Keyword(s):

Negative Impact ◽

Route Planning ◽

Freight Transport ◽

Total System ◽

City Network ◽

Upper Level ◽

The Cost ◽

The Impact ◽

The City ◽

Freight Vehicles

The impact of freight transport in cities is significant, and as such correct planning and management thereof help reduce their enormous negative impact. Above all, the special large vehicles have a greater impact than the remainder of freight vehicles, so a special attention should be paid to them. The vehicles which supply or pick up large amounts of goods at specific points throughout the city are an example of this type of vehicles. The aim of this paper is to minimize the cost of this freight transport type from a social, economic, and environmental viewpoint. To this effect, an optimization model has been proposed based on bilevel mathematical programming which minimizes the total system costs. City network model data are obtained on the lower level such as vehicle flow and travelling times, which are then used on the upper level to calculate total system costs. The model has been applied to a real case in Santander (Spain), whose final result shows the size and typology of the fleet of vehicles necessary to have the least impact on the city. The greater the vehicles size is (i.e., using fewer trucks), the less the cost of the freight transport is.

Download Full-text

Prediction of the thermal conductivities of wood based on an intelligent algorithm

BioResources ◽

10.15376/biores.16.1.1161-1185 ◽

2020 ◽

Vol 16 (1) ◽

pp. 1161-1185

Author(s):

Shiyu Zhou ◽

Xiaoxia Yang ◽

Yandong Zhang ◽

Xiaoping Liu ◽

Yucheng Zhou

Keyword(s):

Thermal Conductivity ◽

Conventional Heating ◽

Theoretical Formula ◽

Support Vector ◽

Intelligent Algorithm ◽

Heating Method ◽

Intelligent Algorithms ◽

Thermal Physical Properties ◽

Floor Heating ◽

Thermal Conductivities

For thermal comfort and energy-saving performance, a floor-heating method is superior to conventional heating modes, e.g., radiator, fan coil, etc. The floor-heating method has been developed to be a primary indoor heating form. Wood is the most common floor surface material. Due to the anisotropy of wood, it is difficult to obtain a general theoretical formula for its thermal physical properties. In this paper, intelligent algorithms were adopted to predict thermal conductivities of wood. First, the study elaborated frequently used testing methods of thermal conductivity. Next, 130 types of common wood species were measured to form a database of thermal properties. With this database, intelligent algorithms were used to make predictions. For the thermal conductivity predictions that were conducted with support vector machine, the degree of fit between the predicted results and the measured results was not less than 0.87 (k-fold validation). This study validated the feasibility of the usage of the intelligent algorithm for the research and prediction of the thermal conductivities of wood.

Download Full-text

Development of the Adaptive Fuzzy Control System for a Parallel-Flow Drying Drum

E3S Web of Conferences ◽

10.1051/e3sconf/202128801024 ◽

2021 ◽

Vol 288 ◽

pp. 01024

Author(s):

E. A. Muravyova ◽

A. E. Listunova ◽

S. Sh. Iskakova ◽

A. B. Kaziyeva ◽

A. N. Abdigaliyeva

Keyword(s):

Fuzzy Control ◽

Raw Materials ◽

Adaptive Fuzzy Control ◽

Control Object ◽

Parallel Flow ◽

Practical Significance ◽

Adaptive Fuzzy ◽

Low Efficiency ◽

Drying Technology ◽

The Cost

The process of removing liquid from the surface or inner layers of materials is widely used by various enterprises. To implement such a process, such a method of dehydration as drying is most often used. In drying technology, drum dryers are the most common type. Controlling a drum dryer causes problems such as low efficiency (0.4-0.6) and high operating costs. To eliminate these problems, it is proposed to develop a system of adaptive fuzzy control of a continuous-flow drum dryer in order to increase the efficiency of control of technological processes of drying sand by using intelligent technologies. The method for this article is adaptive control using fuzzy logic control, which has the ability to control the parameters of the dryer depending on changes in the parameters of the control object or external disturbances acting on the control object. Adaptive fuzzy controllers are created on the basis of the proposed method. A model of the control object has been developed taking into account the links between the parameters of the technological regime. The processing of the research results was carried out using the MatLab software. The practical significance of the article lies in the fact that the results can be used in enterprises where parallel-flow drying drums are used to obtain a product of the highest quality, as well as to reduce the cost of purchasing raw materials.

Download Full-text

Intelligent Cloud Workflow Management and Scheduling Method for Big Data Applications

10.21203/rs.2.19246/v1 ◽

2019 ◽

Author(s):

Yannian Hu ◽

Hui Wang ◽

Wenge Ma

Keyword(s):

Big Data ◽

Workflow Management ◽

Optimal Solution ◽

Cloud Service ◽

Pso Algorithm ◽

Average Increase ◽

Combination Strategy ◽

Intelligent Algorithms ◽

Ga Algorithm ◽

Better Than

Abstract With the application and comprehensive development of big data, the need for effective research on cloud workflow management and scheduling is becoming more and more urgent. However, there are currently suitable methods for effective analysis. In order to find out how to effectively manage and schedule smart cloud workflows, the article studies big data from different aspects and draws the following conclusions: Compared with the original JStorm system, the average response time is shortened by up to 58.26%, and the average is shortened. 23.18%; CPU resource utilization increased by 17.96%, an average increase of 11.39%; memory utilization increased by 88.7%, an average increase of 71.16%. In optimizing the dynamic combination of web services, the overall performance of MOACO algorithm and CCA algorithm is better than GA algorithm, and the average performance of MOACO algorithm is better than CCA algorithm. The paper also proposes a cloud workflow scheduling strategy based on intelligent algorithms and adjusting the perceived cloud service resource combination strategy to realize two-layer scheduling of cloud workflow tasks. We have studied three representative intelligent algorithms (ACO algorithm, PSO algorithm and GA algorithm) and designed and improved them for scheduling optimization. It can be clearly seen that in the same scenario, in different test cases the optimal values of the different algorithms vary greatly. However, the optimal solution curve is substantially consistent with the trend of the mean curve.

Download Full-text

Use of mathematical laws for optimizing the dose of swollen and dry bentonite during the fining of white wines. Part II : influence on the volume of lies and economics

OENO One ◽

10.20870/oeno-one.2003.37.2.945 ◽

2003 ◽

Vol 37 (2) ◽

pp. 123

Author(s):

Richard Marchal ◽

S. Weingartner ◽

Philippe Jeandet ◽

Franck Chatelain

Keyword(s):

Power Law ◽

White Wine ◽

White Wines ◽

Good Relationship ◽

Exponential Law ◽

Low Efficiency ◽

The Cost ◽

Higher Doses

A Sauvignon white wine was fined with a dry bentonite (BS), e.g directly incorporated in the wine without swelling treatment, or with the same bentonite swelled in water 24 hours before utilization (BG). The volumes of lees generated by the fining were situated between 0,27 and 1,51 % (v/v) for BS, and between 1,07 and 4,59 % (v/v) for BG. The relation between the quantity of bentonite introduced in the wine (g/hl) and the volume of lees (v/v) follows a power law. The volume of lees only increased by 70 % when the dose of swelled bentonite was doubled; for higher doses of bentonite (rarely used), one can observe a packing of the lees. For BS, lees were approximately twice more volumetric when the dose was doubled. We also observe very good relationship between the clarifying efficiency and the volume of lees. When the clarifying efficiency of BG increased by 10 % the volume of lees increased by 74 %. For BS, when the clarifying efficiency increased by 10 % the volume of lees increased by 86 % because of its low efficiency during clarification. The decrease of the natural proteic haze risk and the volume of lees generated by bentonite fining were also closely correlated by an exponential law. For BG, the mathematical law showed that when the volume of lees increased by 0,1 % (v/v), colloidal haze risk decreased only by 22 %. On the contrary, for BS, when the volume of lees increased by 0,1 %, proteic haze risk decreased by 44 %. Finally, the estimation of the cost of fining showed that the use of a non swelled bentonite was economically more interesting than the utilization of a swelled bentonite. This was true when this Sauvignon wine is sold both in bottle or in bulk. For the studied wine, the estimated winning was 115 euros for 10 hl sold in bulk.

Download Full-text