scholarly journals A Decision-Making Model on the Impact of Vehicle Use on Urban Safety

2021 ◽  
Vol 13 (6) ◽  
pp. 3585
Author(s):  
Dariusz Masłowski ◽  
Małgorzata Dendera-Gruszka ◽  
Ewa Kulińska
Keyword(s):  
Decision Making ◽  
Internal Combustion Engines ◽  
Urban Traffic ◽  
Brake Pads ◽  
Wear And Tear ◽  
Urban Safety ◽  
Negative Impacts ◽  
Urban Conditions ◽  
Decision Making Model ◽  
The Impact

In the current era of urban development, people are already using electric vehicles more and more often for transport purposes, which reduces negative impacts on the environment. However, there are still vehicles in towns and cities that run on ordinary internal combustion engines. Performing optimization measures on the operation of these vehicles improves their performance, which can result in positive sustainable development effects. This article presents measures to reduce the wear and tear of urban vehicles and outlines a decision model to determine which of the vehicle parts described suffer the most frequent wear and tear under urban conditions. The article presents a list of structural elements that are most affected by urban traffic, as well as corrective actions to improve such specialized vehicles. Based on the decision analysis, Rule 1 was eliminated as having the least significant impact on vehicle wear and tear, and the least significant impact on urban safety. On the other hand, the most worn-out elements were found to be gearboxes, clutches, bus levelling electronics, and brake pads and discs. The decision-making model made it possible to identify the factors which have the greatest impact on reducing safety in urban spaces.

A decision making model based on fuzzy inference to predict the impact of SCOR® indicators on customer perceived value

2020 ◽  
Vol 223 ◽  
pp. 107520
Author(s):  
Lucas Gabriel Zanon ◽  
Rafael Ferro Munhoz Arantes ◽  
Lucas Daniel Del Rosso Calache ◽  
Luiz Cesar Ribeiro Carpinetti
Keyword(s):  
Decision Making ◽  
Fuzzy Inference ◽  
Perceived Value ◽  
Model Based ◽  
Customer Perceived Value ◽  
Decision Making Model ◽  
The Impact

The impact on clinical practice of the 2015 reforms to the New South Wales Mental Health Act

2016 ◽  
Vol 25 (1) ◽  
pp. 43-47 ◽  
Author(s):  
Christopher James Ryan ◽  
Sascha Callaghan
Keyword(s):  
Mental Health ◽  
Decision Making ◽  
Clinical Practice ◽  
Persons With Disabilities ◽  
Mental Health Act ◽  
Recovery Movement ◽  
South Wales ◽  
Management Plans ◽  
Decision Making Model ◽  
The Impact

Objectives: The Mental Health Act 2007 (NSW) ( MHA) was recently reformed in light of the recovery movement and the United Nations Convention on the Rights of Persons with Disabilities. We analyse the changes and describe the impact that these reforms should have upon clinical practice. Conclusions: The principles of care and treatment added to the MHA place a strong onus on clinicians to monitor patients’ decision-making capacity, institute a supported decision-making model and obtain consent to any treatment proposed. Patients competently refusing treatment should only be subject to involuntary treatment in extraordinary circumstances. Even when patients incompetently refuse treatment, clinicians must make every effort reasonably practicable to tailor management plans to take account of any views and preferences expressed by them or made known via friends, family or advance statements.

scholarly journals Decision-Making of Underwater Cooperative Confrontation Based on MODPSO

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 2211
Author(s):  
Na Wei ◽  
Mingyong Liu ◽  
Weibin Cheng
Keyword(s):  
Decision Making ◽  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Communication Delay ◽  
Discrete Particle Swarm Optimization ◽  
Swarm Optimization ◽  
Discrete Particle ◽  
Multi Objective ◽  
Decision Making Model ◽  
The Impact

This paper proposes a multi-objective decision-making model for underwater countermeasures based on a multi-objective decision theory and solves it using the multi-objective discrete particle swarm optimization (MODPSO) algorithm. Existing decision-making models are based on fully allocated assignment without considering the weapon consumption and communication delay, which does not conform to the actual naval combat process. The minimum opponent residual threat probability and minimum own-weapon consumption are selected as two functions of the multi-objective decision-making model in this paper. Considering the impact of the communication delay, the multi-objective discrete particle swarm optimization (MODPSO) algorithm is proposed to obtain the optimal solution of the distribution scheme with different weapon consumptions. The algorithm adopts the natural number coding method, and the particle corresponds to the confrontation strategy. The simulation result shows that underwater communication delay impacts the decision-making selection. It verifies the effectiveness of the proposed model and the proposed multi-objective discrete particle swarm optimization algorithm.

Grey target decision-making model of interval grey number based on cone volume

2017 ◽  
Vol 7 (2) ◽  
pp. 247-258 ◽  
Author(s):  
Lizhen Wang ◽  
Wuyong Qian
Keyword(s):  
Decision Making ◽  
Entropy Method ◽  
Maximal Entropy ◽  
Information Distortion ◽  
Content Type ◽  
Model Based ◽  
Proposed Model ◽  
Grey Number ◽  
Decision Making Model ◽  
The Impact

Purpose The purpose of this paper is to propose a grey target decision model based on cobweb area in order to overcome the effect and influence from the extreme value of the index on the decision result. However, it does not take into account the impact of the correlation between indicators on the angle of the index, and produce a certain degree decision information distortion as a result of the equal angle between the indicators. In order to solve the above problems, a novel grey decision-making model based on cone volume is proposed. Design/methodology/approach In this paper, the model uses the whitening weight function to whiten the interval grey number, and the Delphi method and the maximal entropy method are exploited to integrate the weight of the index. On the basis of this, the center of the bull’s eye, the weight and the index value are constructed as the center circle, the radius, and the high cone, respectively. The scheme is selected by the volume of the cone, the decision is made according to the order relation, and the example is utilized to prove and analyze the validity of the proposed model. Findings The results show that the proposed model can well improve the traditional grey target decision-making model from the modeling object and modeling method. Practical implications The method exposed in the paper can be used to deal with the grey target decision-making problems which characteristics are multi-indexes, and the attribute values are interval grey numbers. Originality/value The paper succeeds in overcoming the disadvantages of grey target decision making based on the target center distance and the cobweb area.

scholarly journals A Decision-Making Model Using Machine Learning for Improving Dispatching Efficiency in Chengdu Shuangliu Airport

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Yingmiao Qian ◽  
Shuhang Chen ◽  
Jianchang Li ◽  
Qinxin Ren ◽  
Jinfu Zhu ◽  
...  
Keyword(s):  
Decision Making ◽  
Queuing Theory ◽  
Cost Benefit Analysis ◽  
Cost Benefit ◽  
Urban Traffic ◽  
Mathematical Methods ◽  
Huge Impact ◽  
Neural Network Algorithm ◽  
The Cost ◽  
Decision Making Model

Due to the increasing number of people traveling by air, the passenger flow at the airport is increasing, and the problem of passenger drop-off and pickup has a huge impact on urban traffic. The difficulty of taking a taxi at the airport is still a hot issue in the society. Aiming at the problem of optimizing the allocation of taxi resource, this paper is based on the cost-benefit analysis method to determine the factors that affect the taxi driver’s decision-making. The mathematical methods such as function equation, BP neural network algorithm, and queuing theory were used to establish a complete decision-making model for taxi drivers and an optimization model of dispatching efficiency at the airport. A conclusion has been drawn that the allocation of airport taxi resource should be arranged closely related to drivers’ revenue and the layout of airport line.

Charles E. Lindblom, “The Science of Muddling Through”

2016 ◽  
Author(s):  
Andrea Migone ◽  
Michael Howlett
Keyword(s):  
Public Policy ◽  
Decision Making ◽  
Punctuated Equilibrium ◽  
Policy Decision ◽  
Policy Sciences ◽  
Marginal Analysis ◽  
Policy Decision Making ◽  
Decision Making Model ◽  
The Impact

This chapter discusses “The Science of Muddling Through”, a 1959 paper by Charles E. Lindblom that has influenced several generations of thinking about public policy decision-making in complex situations such as government and bureaucracy. The focus of Lindblom’s paper is on incrementalism, which he originally developed in the early 1950s as a decision-making model. Incrementalism refers to the study of “muddling through” behavior on the part of actual administrators and executives and is also called the method of “successive limited comparison” or “marginal” analysis by Lindblom. This chapter examines the impact of “The Science of Muddling Through” on the development of incrementalism and decision-making studies in the policy sciences. It also considers the influence of incrementalism on budgeting and management and on “punctuated equilibrium” thinking about decision-making outcomes. It concludes with an analysis of criticisms against incrementalism.

scholarly journals An Efficient Ensemble VTOPES Multi-Criteria Decision-Making Model for Sustainable Sugarcane Farms

2019 ◽  
Vol 11 (16) ◽  
pp. 4288 ◽  
Author(s):  
N Deepa ◽  
Durai Raj Vincent P M ◽  
Senthil Kumar N ◽  
Kathiravan Srinivasan ◽  
Chuan-Yu Chang ◽  
...  
Keyword(s):  
Decision Making ◽  
Sustainable Agriculture ◽  
Rank Correlation ◽  
Correlation Method ◽  
Vital Role ◽  
Average Yield ◽  
Yield Data ◽  
Rank Correlation Method ◽  
Decision Making Model ◽  
The Impact

The role of Information Technology based decision models for sustainable agriculture has gained immense prominence in recent years. Ranking of agriculture farms based on their yield plays a vital role in sustainable agriculture. In this work, an ensemble decision-making model, namely VIKOR (Vlsekriterijumska Optimizacija I Kompromisno Resenje), TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution), entropy, and standard deviation (VTOPES), is proposed for ranking the sustainable sugarcane farms. VTOPES system model comprises of four significant steps: (i) determination of significance scores of the sub-parameters, (ii) transformation of sub-parameter sequences into main parameter values, (iii) computation of significant scores of main parameters, and (iv) generation of assessment values and deploying it for ranking the sugarcane farms. The ranking results of the proposed VTOPES model are compared with the ranking patterns obtained from five years average yield data acquired from the selected sugarcane farms. Moreover, the outcomes of the VTOPES model are also compared with other prevalent methods. Subsequently, Spearman’s rank correlation method is applied for evaluating the impact of correlation of VTOPES ranks in comparison with the average yield ranks. Thus, it can be noticed that the empirical results of the VTOPES model provide reliable and sustainable results. Therefore, it suffices to be a sustainable decision model for any problem where multiple parameters are involved.

scholarly journals A dual factor decision making model in green manufacturing

2021 ◽  
Author(s):  
Bahador Jamshidy
Keyword(s):  
Decision Making ◽  
Goal Programming ◽  
Product Information ◽  
Positive Impact ◽  
Green Manufacturing ◽  
Product Recovery ◽  
Market Demand ◽  
Decision Making Model ◽  
Second Category ◽  
The Impact

This study focuses on the evaluation of different methods of product recovery for GM. The evaluation is conducted through the application of a decision making model. The model evaluates product recovery options on the basis of two categories: optimization of objective factors and market demand. The first category in the model focuses on optimization of five objective factors, including environmental impact (E), cost (C), quality (Q), resource consumption (R), and time (T). Goal programming is used to solve the optimization problem. The goal programming is supported by the construction of a decision making tree with three branches: remanufacturing, refurbishing, and current manufacturing. The solution of the decision tree helps determine the best method of product recovery for GM. The second category in the model focuses on the evaluation of market demand. This further supports the selection of the best method for product recovery. To evaluate market demand, a Bayesian forecasting model is used in the construction of a decision making tree. The study shows that the availably of products information including the objective factors and market demand, has a positive impact on making product recovery decisions. It also shows how recovery decisions can be modeled in decision making tress to represent the impact of product information on those decisions.

scholarly journals Study on Grey Correlation Degree Decision-Making Model for Investment Scheme on High-Grade Highways in Western China

2020 ◽  
Vol 2020 ◽  
pp. 1-19
Author(s):  
Huihong Feng ◽  
Tian Tang ◽  
Guohong Zhang ◽  
Li Lu
Keyword(s):  
Decision Making ◽  
Influencing Factors ◽  
Western China ◽  
High Grade ◽  
Grey Correlation ◽  
Western Area ◽  
Correlation Degree ◽  
Grey Correlation Degree ◽  
Decision Making Model ◽  
The Impact

Under the impact of the government’s policies to expand domestic demand and maintain economic growth, the western area acquired a large amount of funding for infrastructure construction. The high-grade highways became the key project attracting investment because of its great development potential and strong transportation adaptability. However, the special geographical conditions in the western area created numerous barriers for the construction of high-grade highways, including many investment influencing factors, great investment risks and uncertainties, and high difficulty in defining the investment effect. In view of the goals in technical advancement and economic rationality for the investment scheme of high-grade highways, the possible influencing factors of the investment scheme decision-making of the high-grade highways in western China were first given comprehensive analysis. Through literature review and field investigation, 67 influencing factors of investment scheme decision-making were determined by the cost decomposition method and expert investigation method. Then, the influence degree of each factor was analyzed by using the Delphi method and entropy method. According to the sorting results, 49 important factors were reserved as the detailed index for investment scheme decision-making. Afterwards, the index system for investment scheme decision-making consisting of 2 target factors, 5 first-level indexes, 13 second-level indexes, and 49 third-level indexes was constructed. Based on this, the decision-making model of investment scheme for high-grade highways was established by combining Analytic Hierarchy Process (AHP) and grey theory. Specially, the standardized index matrix of investment scheme was determined by AHP, and the relation degree of each scheme was calculated by grey correlation degree, and then the optimal scheme was shaped by the size of comprehensive relation degree. Finally, the grey correlation degree decision-making model of the investment scheme was applied to a highway project located in Gansu province, China. The results showed that the optimal investment scheme determined by the decision model was consistent with the scheme actually adopted, indicating that the model has good operability and practicability. In this paper, a grey correlation degree decision-making model of investment scheme for high-grade highways in western China was proposed, providing an effective theoretical basis and valuable practical experience for the investment scheme decision-making of transportation infrastructure under special environments.

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