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What is the primary consideration in route selection for a multimodal transportation system?
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Transport cost, time, and inherent risks |
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Route selection strategy has become the main aspect in the multimodal transportation system. The transport cost and time as well as the inherent risks must be considered when determining a corrective design plan.
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A. Kengpol, S. Tuammee, and M. Tuominen, The development of a framework for route selection in multimodal transportation, Int. J. Logist. Manag., Vol. 25, 2015, pp. 581-610.
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Which decision-making approach is utilized to determine the optimal multimodal transportation route in the proposed model?
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Analytic Hierarchy Process (AHP) and Zero-One Goal Programming (ZOGP) |
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This paper develops a decision support model using an analytic hierarchy process (AHP) and zero-one goal programing (ZOGP) to determine an optimal multimodal transportation route.
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A. Kengpol, S. Tuammee, and M. Tuominen, The development of a framework for route selection in multimodal transportation, Int. J. Logist. Manag., Vol. 25, 2015, pp. 581-610.
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What does AHP stand for in the context of the decision support model?
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Analytic Hierarchy Process |
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This paper develops a decision support model using an analytic hierarchy process (AHP) and zero-one goal programing (ZOGP) to determine an optimal multimodal transportation route.
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A. Kengpol, S. Tuammee, and M. Tuominen, The development of a framework for route selection in multimodal transportation, Int. J. Logist. Manag., Vol. 25, 2015, pp. 581-610.
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What is the objective of the zero-one goal programming (ZOGP) in the model?
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To generate the optimal multimodal transportation route |
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This paper develops a decision support model using an analytic hierarchy process (AHP) and zero-one goal programing (ZOGP) to determine an optimal multimodal transportation route.
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A. Kengpol, S. Tuammee, and M. Tuominen, The development of a framework for route selection in multimodal transportation, Int. J. Logist. Manag., Vol. 25, 2015, pp. 581-610.
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Essay | Explanation: ZOGP is used to generate the optimal route by integrating weights obtained from AHP.
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ZOGP can be used to select the alternatives because of the binary nature of the selection variables and the multiple conflicting criteria involved. The ZOGP model has been applied very frequently because it is simple to use and understand |
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ZOGP can be used to select the alternatives because of the binary nature of the selection variables and the multiple conflicting criteria involved. The ZOGP model has been applied very frequently because it is simple to use and understand
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R.-S. Chen and J.Z. Shyu, Selecting a weapon system using zero-one goal programming and analytic network process, J. Inf. Optim. Sci., Vol. 27, 2006, pp. 379-399.
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What are the main drivers for the increasing focus on multimodal transportation in logistics systems?
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Environmental concerns, road safety issues, and traffic congestion |
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However, there are major challenges in the development of multimodal transportation associated with inherent risks and numerous uncertainties.
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A. Kengpol and S. Tuammee, "The development of a decision support framework for a quantitative risk assessment in multimodal green logistics: An empirical study", Int. J. Prod. Res., vol. 54, no. 4, pp. 1020-1038, Feb. 2016.
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Why is comprehensive risk analysis considered crucial in the development of multimodal transportation?
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To minimize environmental concerns |
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Since risks are potential threats that directly impact logistics and transportation systems, comprehensive risk analysis should be carried out. Risk analysis is a critical process of identifying and analyzing significant issues to help industry mitigate those risks.
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1. J. Vilko, P. Ritala and J. Hallikas, "Risk management abilities in multimodal maritime supply chains: Visibility and control perspectives", Accident Anal. Prevention, vol. 123, pp. 469-481, Feb. 2019.
2. A. Kengpol and S. Tuammee, "The development of a decision support framework for a quantitative risk assessment in multimodal green logistics: An empirical study", Int. J. Prod. Res., vol. 54, no. 4, pp. 1020-1038, Feb. 2016.
3. R. Z. Farahani, Logistics Operations Management: Concepts Models, New York, NY, USA:Elsevier, 2011.
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What is the primary challenge in identifying and prioritizing risks in multimodal transportation?
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Ambiguity of relevant data |
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However, there are major challenges in the development of multimodal transportation associated with inherent risks and numerous uncertainties. Since risks are potential threats that directly impact logistics and transportation systems, comprehensive risk analysis should be carried out.
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3. J. Vilko, P. Ritala and J. Hallikas, "Risk management abilities in multimodal maritime supply chains: Visibility and control perspectives", Accident Anal. Prevention, vol. 123, pp. 469-481, Feb. 2019.
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Which methodology is proposed for risk analysis in multimodal transportation in this study?
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Fuzzy Analytic Hierarchy Process (FAHP) and Data Envelopment Analysis (DEA) |
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This study proposes the integration of the fuzzy analytic hierarchy process (FAHP) and data envelopment analysis (DEA) for identifying and assessing quantitative risks.
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A. Karamoozian, D. Wu, C. L. P. Chen and C. Luo, "An approach for risk prioritization in construction projects using analytic network process and decision making trial and evaluation laboratory", IEEE Access, vol. 7, pp. 159842-159854, 2019.
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Essay | Discuss the significance of comprehensive risk analysis in the development of multimodal transportation. And explain how the proposed FAHP-DEA methodology contributes to identifying and prioritizing risks in this context.
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However, identifying and prioritizing risks is more complex because of the ambiguity of the relevant data. This study proposes the integration of the fuzzy analytic hierarchy process (FAHP) and data envelopment analysis (DEA) for identifying and assessing quantitative risks. |
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However, identifying and prioritizing risks is more complex because of the ambiguity of the relevant data. This study proposes the integration of the fuzzy analytic hierarchy process (FAHP) and data envelopment analysis (DEA) for identifying and assessing quantitative risks.
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Q. Shi, Y. Zhou, C. Xiao, R. Chen and J. Zuo, "Delivery risk analysis within the context of program management using fuzzy logic and DEA: A China case study", Int. J. Project Manage., vol. 32, no. 2, pp. 341-349, Feb. 2014.
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What is the significance of the Jammu-Srinagar National Highway in the context of the region?
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It serves as a critical road connection between Kashmir valley and the rest of India |
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The Jammu-Srinagar National Highway is the critical road connection between Kashmir valley and the rest of India. It passes through extremely steep slopes and high mountains prone to mass movements, particularly landslides and rockslides.
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The Jammu-Srinagar National Highway is the critical road connection between Kashmir valley and the rest of India. It passes through extremely steep slopes and high mountains prone to mass movements, particularly landslides and rockslides.
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What are the primary challenges associated with the Jammu-Srinagar National Highway?
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Landslides and rockslides, particularly in steep slopes and high mountains |
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The Jammu-Srinagar National Highway is the critical road connection between Kashmir valley and the rest of India. It passes through extremely steep slopes and high mountains prone to mass movements, particularly landslides and rockslides.
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Identifying the parameters responsible for landslides on NH-44 Jammu Srinagar national highway for early warning system
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Why does the highway experience continuous blockades, especially during winters?
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Frequent snowfall and landslide-prone sites |
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Many landslide-prone sites along the Highway are responsible for the continuous blockade almost throughout the year but peaking particularly during winters.
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GIS techniques and statistical models in evaluating landslide hazard
Shallow landslide hazard assessment using a physically based model and digital elevation data
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What is the objective of the present study regarding the Jammu-Srinagar National Highway?
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Characterizing factors triggering landslides and assessing future landslide events |
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This study aims to use various field-based geotechnical parameters such as direct shear, natural density, atterberg limits (plastic limit, liquid limit, plasticity index), moisture content, and specific gravity) along the land surface temperature (LST) and rainfall information for modeling the occurrences of landslides in the study area.
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Management of landslides in a rural–urban transition zone using machine learning algorithms—a case study of a national highway (NH-44), India, in the rugged Himalayan terrains
Comprehensive study on evaluation of Kaliasaur Landslide attributes in Garhwal Himalaya by the execution of geospatial, geotechnical and geophysical methods
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Essay | Discuss the major challenges faced by the Jammu-Srinagar National Highway and how landslides impact the region's economy. Explain the importance of the study in addressing these challenges and proposing effective countermeasures.
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The frequent landslides on National Highway often remain closed, affecting the state's economy and claiming precious lives due to landslides and shooting stones. |
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The frequent landslides on National Highway often remain closed, affecting the state's economy and claiming precious lives due to landslides and shooting stones. The responsible factors and the critical threshold values responsible for triggering landslides are identified using field investigation, geotechnical investigation, geo-laboratory testing, and Remote Sensing techniques.
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Modeling on comparison of ecosystem services concepts, tools, methods and their ecological-economic implications: a review
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What is the primary focus of the research mentioned in the passage?
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Preparing and evaluating landslide susceptibility maps |
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As a result, landslide assessment using different methods in different geographical regions has significant importance.
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1. Landslide susceptibility mapping using bivariate statistical models and GIS in chattagram district, Bangladesh
2. Landslide susceptibility mapping using diferent GIS-based bivariate models
3. Landslide susceptibility assessment in complex geological settings: sensitivity to geological information and insights on its parameterization
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How many machine learning algorithms were used for landslide susceptibility mapping in the research?
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Three |
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The research aims to prepare and evaluate landslide susceptibility maps (LSMs) of the Chattogram district using three machine learning algorithms of Logistic Regression (LR), Random forest (RF) and Decision and Regression Tree (DRT)
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1. Landslide susceptibility mapping using machine learning algorithms and comparison of their performance at Abha Basin, Asir Region, Saudi Arabia
2. Landslide susceptibility mapping using GIS-based machine learning algorithms for the Northeast Chongqing Area, China
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What are the key factors considered for landslide susceptibility mapping in the research?
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All of the above |
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Besides, some topographic (elevation, slope and aspect) and hydrologic (TRI and stream density) factors also cause landslides accompanied by geology. Human interventions such as LULC and road construction have a minor impact compared to other factors.
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1. Integrating vegetation indices and geo-environmental factors in GIS-based landslide-susceptibility mapping: using logistic regression
2. Slope unit-based landslide susceptibility mapping using certainty factor, support vector machine, random forest, CF-SVM and CF-RF models
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What percentage of the Chattogram district is identified as highly susceptible to landslides according to the LSMs?
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9–12% |
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The LSMs showed that almost 9–12 % of areas of the Chattogram district are highly susceptible to landslides.
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1. Comparison of random forest model and frequency ratio model for landslide susceptibility mapping (LSM) in Yunyang County (Chongqing, China)
2. A novel ensemble approach for landslide susceptibility mapping (LSM) in Darjeeling and Kalimpong districts, West Bengal, India
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Essay | Discuss the significance of landslide susceptibility mapping in the context of hazard management. How can the prepared maps be applied at the local scale for effective landslide risk reduction and mitigation in the Chattogram district?
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Among the models, LR showed the highest prediction rate and DRT showed the highest success rate. According to susceptibility zones, DRT is the more realistic model followed by LR. The maps can be applied at the local scale for landslide hazard management. |
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Among the models, LR showed the highest prediction rate and DRT showed the highest success rate. According to susceptibility zones, DRT is the more realistic model followed by LR. The maps can be applied at the local scale for landslide hazard management.
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1. A review on spatial, temporal and magnitude prediction of landslide hazard
2. Evaluating machine learning and statistical prediction techniques for landslide susceptibility modeling
3. Prediction of the landslide susceptibility: which algorithm, which precision?
4. Validation of spatial prediction models for landslide hazard mapping
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