Shortest Route at Dynamic Location with Node Combination-Dijkstra Algorithm

Online transportation has become a basic requirement of the general public in support of all activities to go to work, school or vacation to the sights. Public transportation services compete to provide the best service so that consumers feel comfortable using the services offered, so that all activities are noticed, one of them is the search for the shortest route in picking the buyer or delivering to the destination. Node Combination method can minimize memory usage and this methode is more optimal when compared to A* and Ant Colony in the shortest route search like Dijkstra algorithm, but can't store the history node that has been passed. Therefore, using node combination algorithm is very good in searching the shortest distance is not the shortest route. This paper is structured to modify the node combination algorithm to solve the problem of finding the shortest route at the dynamic location obtained from the transport fleet by displaying the nodes that have the shortest distance and will be implemented in the geographic information system in the form of map to facilitate the use of the system

A taxonomy for emergency service station location problem

The emergency service station (ESS) location problem has been widely studied in the literature since 1970s. There has been a growing interest in the subject especially after 1990s. Various models with different objective functions and constraints have been proposed in the academic literature and efficient solution techniques have been developed to provide good solutions in reasonable times. However, there is not any study that systematically classifies different problem types and methodologies to address them. This paper presents a taxonomic framework for the ESS location problem using an operations research perspective. In this framework, we basically consider the type of the emergency, the objective function, constraints, model assumptions, modeling, and solution techniques. We also analyze a variety of papers related to the literature in order to demonstrate the effectiveness of the taxonomy and to get insights for possible research directions

Planning Emergency Shelters for Urban Disasters: A Multi-Level Location–Allocation Modeling Approach

In recent years, cities are threatened by various natural hazards. Planning emergency shelters in advance is an effective approach to reducing the damage caused by disasters and ensuring the safety of residents. Thus, providing the optimal layout of urban emergency shelters is an important stage of disaster management and an act of humanitarian logistics. In order to study the optimal layout of emergency shelters in small mountain cities, this paper constructs multi-level location models for different grades of emergency shelters so as to minimize the travel and construction costs and maximize the coverage rate. Specifically, the actual service of emergency shelters is determined using Geographic Information System (GIS) software and Weighted Voronoi Diagram (WVD) models under the limitation of site capacity, and the space layout is adjusted through combining the actual urban land with the construction position. In this paper, the Jianchuan county seat at Yunnan Province, China, was considered as a case study to illustrate the models of emergency shelters in which the feasibility of the presented models is verified. The proposed research methods and models have provided theoretical basis and a benchmark for the optimal layout of emergency shelters in other small mountain cities

The Influence of Land Cover on the Spatial Distribution of Fire Sites: A Case Study of Łódzkie Voivodeship, Poland

The paper continues from previous joint studies and their practical application at the confluence of human geography, safety-related research and Geographic Information Systems (GIS). The objective of the study was to identify the land cover types most at risk from fire. The study has contributed an original angle by taking into account various land cover types with a potential influence on the distribution of fires geocoded at the address level. The analysis considered 27,651 fire interventions, as recorded by the Polish State Fire Service between 2014 and 2016 in the country’s central region known as Łódzkie Voivodeship. The main methods employed include various GIS tools, including Voronoi tessellation (to identify the areas most at risk of fire) and the fire location quotient (FLQ, a measure of the colocation between the number of fires and land cover). The most important conclusion is that of all the land cover types considered in the study, the built-up area type, especially the multi-family residential and retail and service area subtypes, was virtually the only one with a strong influence on the location of fires. The fire high-risk areas (FH-RA) identified here were primarily limited to urban areas.The paper continues from previous joint studies and their practical application at the confluence of human geography, safety-related research and Geographic Information Systems (GIS). The objective of the study was to identify the land cover types most at risk from fire. The study contributes an original angle by taking into account various land cover types with a potential influence on the distribution of fires geocoded at the address level. The analysis takes into account 27,651 fire interventions, as recorded by the Polish State Fire Service between 2014 and 2016 in the country’s central region known as Łódzkie Voivodeship. The main methods employed include various GIS tools, including Voronoi tessellation (to identify the areas most at risk of fire) and the fire location quotient (FLQ, a measure of colocation between the number of fires and land cover). The most important conclusion is that of all the land cover types considered in the study, the built-up area type, especially the multi-family residential and retail and service area subtypes, was virtually the only one with a strong influence on the location of fires. The fire high-risk areas (FH-RA) identified here were primarily limited to urban areas

A Tutorial on Geographic Information Systems: A Ten-year Update

This tutorial provides a foundation on geographic information systems (GIS) as they relate to and are part of the IS body of knowledge. The tutorial serves as a ten-year update on an earlier CAIS tutorial (Pick, 2004). During the decade, GIS has expanded with wider and deeper range of applications in government and industry, widespread consumer use, and an emerging importance in business schools and for IS. In this paper, we provide background information on the key ideas and concepts of GIS, spatial analysis, and latest trends and on the status and opportunities for incorporating GIS, spatial analysis, and locational decision making into IS research and in teaching in business and IS curricula

Shortest Route at Dynamic Location with Node Combination-Dijkstra Algorithm

Abstract— Online transportation has become a basic requirement of the general public in support of all activities to go to work, school or vacation to the sights. Public transportation services compete to provide the best service so that consumers feel comfortable using the services offered, so that all activities are noticed, one of them is the search for the shortest route in picking the buyer or delivering to the destination. Node Combination method can minimize memory usage and this methode is more optimal when compared to A* and Ant Colony in the shortest route search like Dijkstra algorithm, but can’t store the history node that has been passed. Therefore, using node combination algorithm is very good in searching the shortest distance is not the shortest route. This paper is structured to modify the node combination algorithm to solve the problem of finding the shortest route at the dynamic location obtained from the transport fleet by displaying the nodes that have the shortest distance and will be implemented in the geographic information system in the form of map to facilitate the use of the system. Keywords— Shortest Path, Algorithm Dijkstra, Node Combination, Dynamic Location (key words