scholarly journals Modeling Method for Cost and Carbon Emission of Sheep Transportation Based on Path Optimization

2020 ◽  
Vol 12 (3) ◽  
pp. 835
Author(s):  
Mengjie Zhang ◽  
Lei Wang ◽  
Huanhuan Feng ◽  
Luwei Zhang ◽  
Xiaoshuan Zhang ◽  
...  
Keyword(s):  
Quantitative Evaluation ◽  
Carbon Emissions ◽  
Evaluation Model ◽  
Optimal Path ◽  
Optimal Solution ◽  
Path Optimization ◽  
Power Cost ◽  
Random Path ◽  
Different Types ◽  
The Cost

Energy conservation, cost, and emission reduction are the research topics of most concern today. The aim of this paper is to reduce the cost and carbon emissions and improve the sustainable development of sheep transportation. Under the typical case of the “farmers–middlemen–slaughterhouses” (FMS) supply model, this paper comprehensively analyzed the factors, sources, and types of cost and carbon emissions in the process of sheep transportation, and a quantitative evaluation model was established. The genetic algorithm (GA) was proposed to search for the optimal path of sheep transportation, and then the model solving algorithm was designed based on the basic GA. The results of path optimization indicated that the optimal solution can be obtained effectively when the range of basic parameters of GA was set reasonably. The optimal solution is the optimal path and the shortest distance under the supply mode of FMS, and the route distance of the optimal path is 245.6 km less than that of random path. From the cost distribution, the fuel power cost of the vehicle, labor cost in transportation, and consumables cost account for a large proportion, while the operation and management cost of the vehicle and depreciation cost of the tires account for a small proportion. The total cost of the optimal path is 26.5% lower than that of the random path, and the total carbon emissions are 36.3% lower than that of random path. Path optimization can thus significantly reduce the cost of different types and significantly reduce the proportion of vehicle fuel power cost and consumables cost, but the degree of cost reduction of different types is different. The result of the optimal path is the key to be explored in this study, and it can be used as the best reference for sheep transportation. The quantitative evaluation model established in this paper can systematically measure the cost and carbon emissions generated in the sheep transportation, which can provide theoretical support for practical application.

scholarly journals Carbon Emission Reduction of Apparel Material Distribution Based on Multi-Objective Genetic Algorithm (NSGA-II)

2019 ◽  
Vol 11 (9) ◽  
pp. 2571
Author(s):  
Xujing Zhang ◽  
Lichuan Wang ◽  
Yan Chen
Keyword(s):  
Genetic Algorithm ◽  
Carbon Emissions ◽  
Optimal Solution ◽  
Material Distribution ◽  
Low Carbon ◽  
Nsga Ii ◽  
Management Objectives ◽  
Multi Objective Genetic Algorithm ◽  
Distribution Process ◽  
The Cost

Low-carbon production has become one of the top management objectives for every industry. In garment manufacturing, the material distribution process always generates high carbon emissions. In order to reduce carbon emissions and the number of operators to meet enterprises’ requirements to control the cost of production and protect the environment, the paths of material distribution were analyzed to find the optimal solution. In this paper, the model of material distribution to obtain minimum carbon emissions and vehicles (operators) was established to optimize the multi-target management in three different production lines (multi-line, U-shape two-line, and U-shape three-line), while the workstations were organized in three ways: in the order of processes, in the type of machines, and in the components of garment. The NSGA-II algorithm (non-dominated sorting genetic algorithm-II) was applied to obtain the results of this model. The feasibility of the model and algorithm was verified by the practice of men’s shirts manufacture. It could be found that material distribution of multi-line layout produced the least carbon emissions when the machines were arranged in the group of type.

A Multiple Level of Detail Approach to the Tactical Movement Problem

2012 ◽  
Vol 6 (6) ◽  
pp. 749-756 ◽  
Author(s):  
Peter Beasley ◽  
◽  
P. Ross McAree
Keyword(s):  
Optimal Path ◽  
Optimal Solution ◽  
Cost Effective ◽  
Multiple Level ◽  
Practical Application ◽  
Robotic Excavator ◽  
The World ◽  
The Cost ◽  
Robotic Agent ◽  
Movement Problem

The tactical movement problemis considered to be one in which a robotic agent is required to move around its world to complete a task. This agent has manipulation abilities which allow it to perform work on its local surroundings. The coupled optimisation of the agent movements and manipulations is thus of key importance to minimise the cost of completing the task. The driving practical application in this paper is one of cost effective excavation in a mining environment. The agent is a mining shovel and it has the ability to manipulate the world through excavation actions. The problem becomes one of determining the optimal path that the shovel should take and the dig operations that should be completed at each point along the path. An initial solution is presented to automatically generate an optimized dig plan for a large robotic excavator. A wavelet based detail reduction approach is used which allows a near optimal solution of the problem to be generated in practically useful timeframes.

scholarly journals Optimization of open flow controller placement in software defined networks

2021 ◽  
Vol 11 (4) ◽  
pp. 3145
Author(s):  
Raghda Salam Al mahdawi ◽  
Huda M. Salih
Keyword(s):  
Network Architecture ◽  
Optimal Solution ◽  
Minimum Cost ◽  
Open Flow ◽  
Processing Power ◽  
Input Size ◽  
Different Types ◽  
Network Topologies ◽  
High Level ◽  
The Cost

The world is entering into the era of Big Data where computer networks are an essential part. However, the current network architecture is not very convenient to configure such leap. Software defined network (SDN) is a new network architecture which argues the separation of control and data planes of the network devices by centralizing the former in high level, centralised devices and efficient supervisors, called controllers. This paper proposes a mathematical model that helps optimizing the locations of the controllers within the network while minimizing the overall cost under realistic constrains. Our method includes finding the minimum cost of placing the controllers; these costs are the network latency, controller processing power and link bandwidth. Different types of network topologies have been adopted to consider the data profile of the controllers, links of controllers and locations of switches. The results showed that as the size of input data increased, the time to find the optimal solution also increased in a non-polynomial time. In addition, the cost of solution is increased linearly with the input size. Furthermore, when increasing allocating possible locations of the controllers, for the same number of switches, the cost was found to be less.

Cutting Path Optimization of Pattern Pieces in Garment Automatic Cutter

2010 ◽  
Vol 129-131 ◽  
pp. 973-977
Author(s):  
Ying Lin Li ◽  
Man Liang Qiu ◽  
Lian He Yang
Keyword(s):  
Optimal Solution ◽  
Optimization Method ◽  
Path Optimization ◽  
Cutting Process ◽  
Cutting Efficiency ◽  
Automatic Optimization ◽  
2D Pattern ◽  
The Cost ◽  
Cutting Path ◽  
Approximate Optimal Solution

In view of the defect and shortage in cutting path automatic optimization of 2D pattern pieces in current garment automatic cutter, a new optimization method of computer is explored. If there is no cutting path optimization implemented by garment automatic cutter before cutting, some problems will be caused, such as too much unless travel and too long processing time. At present, both at home and abroad, the studies on automatic optimization in cutting preprocessing are relatively weak. According to the “segment cutting from left to right” feature of automatic cutter in cutting process, an algorithm which can be summarized as “segment and reducing point” was proposed. This algorithm combined with the solution of shortest path problem, its purpose is to seek for the approximate optimal solution of cutting path. The algorithm implemented through Visual C++ 6.0 programming. Used in production by enterprise shows that the program is simple to operate, and has a high compute speed. Averagely, unless travel in cutting process reduced more than 10%. It proves that the algorithm is feasible and efficient. Using this algorithm achieved the purpose of reducing unless travel, improving cutting efficiency and lowering the cost.

Two- and Three-Dimensional Path Optimization for Production Machinery

1999 ◽  
Vol 122 (1) ◽  
pp. 244-252 ◽  
Author(s):  
W. A. Khan ◽  
D. R. Hayhurst
Keyword(s):  
Optimal Path ◽  
Three Dimensional ◽  
Optimal Solution ◽  
Two Dimensions ◽  
Path Optimization ◽  
Three Dimensions ◽  
Construction Techniques ◽  
Pick And Place ◽  
Discrete Manufacturing ◽  
Problem Instances

Path optimization is desirable in many problem instances occurring in discrete manufacturing and pick and place technology. The problem may refer to applications ranging from two-dimensional movements such as in milling processes to three-dimensional movements required in many robotic operations. The optimal path can be found using tour construction techniques, sub tour elimination techniques and tour to tour improvement techniques. The limits to which these solution methodologies can be applied are restricted to a certain number of nodes. The optimal path for two- and three-dimensional TSP is determined using a stochastic search procedure based on a tour improvement technique. An optimal solution is presented for 500 node TSP in two dimensions. A procedure for finding optimal path for an even larger number of nodes is outlined. The optimal path in three dimensions is also presented using nodes distributed along the periphery of three-dimensional primitives. [S1087-1357(00)71601-7]

An Improved Chaos Electromagnetism Mechanism Algorithm for Path Optimization Problem

2016 ◽  
Vol 3 (2) ◽  
pp. 475
Author(s):  
Shoulin Yin ◽  
Jie Liu ◽  
Lin Teng
Keyword(s):  
Em Algorithm ◽  
Optimal Path ◽  
Main Idea ◽  
Optimal Solution ◽  
Pso Algorithm ◽  
Population Diversity ◽  
Path Optimization ◽  
Continuous Space ◽  
Chaotic Mapping ◽  
Quasi Newton

<p><em>As we all know, traditional electromagnetism mechanism</em><em> </em><em>(EM) algorithm has the disadvantage with low solution precision, lack of mining ability and easily falling into precocity. This paper proposes a new chaos electromagnetism mechanism algorithm combining chaotic mapping with limited storage Quasi-Newton Method</em><em> </em><em>(EM-CMLSQN). Its main idea is that it adopts limit quasi-Newton operator to replace the local optimization operator in EM algorithm for local searching in the late of algorithm. In the process of algorithm, the chaos mapping is introduced into optimization processes, and it generates new individuals to jump out of local to maintain the population diversity according to characteristics of chaos mapping random traversal. Finally, the experiments show that the new algorithm can effectively jump out of local optimal solution through comparing three continuous space test functions. The new algorithm has obvious advantages in terms of convergence speed compared to traditional EM algorithm, in addition, it is more accuracy than particle swarm optimization</em><em> </em><em>(PSO) algorithm. We compare the new chaos electromagnetism mechanism algorithm with ant colony optimization</em><em> </em><em>(ACO) algorithm, PSO algorithm, the results represent that new scheme can obtain the optimal path in the path optimization process, which shows that the new method has better applicability in the discrete domain problem</em>.</p>

OPTIMAL FEASIBLE SOLUTIONS TO A ROAD FREIGHT TRANSPORTATION PROBLEM

2020 ◽  
Vol 5 (1) ◽  
pp. 456
Author(s):  
Tolulope Latunde ◽  
Joseph Oluwaseun Richard ◽  
Opeyemi Odunayo Esan ◽  
Damilola Deborah Dare
Keyword(s):  
Transportation Problem ◽  
Optimal Solution ◽  
Transportation Cost ◽  
North West ◽  
Life Problems ◽  
Basic Feasible Solutions ◽  
Feasible Solutions ◽  
Road Freight Transportation ◽  
The Cost ◽  
Cost Of Transportation

For twenty decades, there is a visible ever forward advancement in the technology of mobility, vehicles and transportation system in general. However, there is no "cure-all" remedy ideal enough to solve all life problems but mathematics has proven that if the problem can be determined, it is most likely solvable. New methods and applications will keep coming to making sure that life problems will be solved faster and easier. This study is to adopt a mathematical transportation problem in the Coca-Cola company aiming to help the logistics department manager of the Asejire and Ikeja plant to decide on how to distribute demand by the customers and at the same time, minimize the cost of transportation. Here, different algorithms are used and compared to generate an optimal solution, namely; North West Corner Method (NWC), Least Cost Method (LCM) and Vogel’s Approximation Method (VAM). The transportation model type in this work is the Linear Programming as the problems are represented in tables and results are compared with the result obtained on Maple 18 software. The study shows various ways in which the initial basic feasible solutions to the problem can be obtained where the best method that saves the highest percentage of transportation cost with for this problem is the NWC. The NWC produces the optimal transportation cost which is 517,040 units.

AGRICULTURAL PERIODICALS OF RUSSIA IN THE EARLY XX CENTURY

2019 ◽  
Keyword(s):  
Statistical Data ◽  
Soil Science ◽  
Agriculture Soil ◽  
Agricultural Knowledge ◽  
Horse Breeding ◽  
Different Types ◽  
Fruit Growing ◽  
Advanced Knowledge ◽  
The Cost ◽  
The Upper Volga Region

The article deals with the distribution of agricultural periodicals on the territory of the Russian Em-pire in the early twentieth century. Before that there were practically no publications on the pages of sci-entific magazines. Great emphasis is placed on the analysis of agricultural magazines published before 1917 in the Upper Volga region, namely in Vladimir, Kostroma, Tver and Yaroslavl provinces. Thanks to existed in pre-revolutionary Russian periodicals on agricultural subjects advanced knowledge of agron-omy, agriculture, soil science, horticulture, fruit growing, vegetable growing, winemaking, viticulture, 135 tobacco growing, livestock, poultry, bee-keeping, veterinary medicine, forestry, and hunting, land man-agement, irrigation, horse breeding were promoted. On the basis of statistical data, office documentation and other published sources, the author draws conclusions about the degree of accessibility of agricul-tural periodicals for the population, including the peasantry. Availability of agricultural periodicals largely depended on its price, so the author studied the situation with the cost of the annual subscription fee of these publications. The article investigates the issues of periodicity of agricultural magazines and newspapers, the exact number of such publications, as well as their subject matter. Existence duration of different types of periodicals is analyzed, the main publishers of magazines and newspapers, places of their publication are revealed. A prominent place is given to the publishing activities of agricultural pub-lic organizations and zemstvo self-government bodies. It is concluded that natural process of agricultural knowledge distribution among the population of Russia through publications on the pages of periodicals was disrupted by revolutionary events of 1917.

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 Game-Theoretic Decision Support for Cyber Forensic Investigations

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5300
Author(s):  
Antonia Nisioti ◽  
George Loukas ◽  
Stefan Rass ◽  
Emmanouil Panaousis
Keyword(s):  
Cyber Security ◽  
Strategic Decisions ◽  
Bayesian Games ◽  
Bayesian Game ◽  
Cyber Forensics ◽  
Detection And Attribution ◽  
Different Types ◽  
Game Theoretic ◽  
The Cost

The use of anti-forensic techniques is a very common practice that stealthy adversaries may deploy to minimise their traces and make the investigation of an incident harder by evading detection and attribution. In this paper, we study the interaction between a cyber forensic Investigator and a strategic Attacker using a game-theoretic framework. This is based on a Bayesian game of incomplete information played on a multi-host cyber forensics investigation graph of actions traversed by both players. The edges of the graph represent players’ actions across different hosts in a network. In alignment with the concept of Bayesian games, we define two Attacker types to represent their ability of deploying anti-forensic techniques to conceal their activities. In this way, our model allows the Investigator to identify the optimal investigating policy taking into consideration the cost and impact of the available actions, while coping with the uncertainty of the Attacker’s type and strategic decisions. To evaluate our model, we construct a realistic case study based on threat reports and data extracted from the MITRE ATT&CK STIX repository, Common Vulnerability Scoring System (CVSS), and interviews with cyber-security practitioners. We use the case study to compare the performance of the proposed method against two other investigative methods and three different types of Attackers.

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