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Traditional optimal route selection procedures in traffic network usually take into account distance and/or travelling time between nodes. These two values are not always directly proportional, but they both influence travelling costs. Most of modern navigational systems dynamically check proposed route in certain time interval and correct it if ne...
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... Among existing literature on the transportation problem of engineering materials, studies about the path optimization problem mainly focus on the optimization algorithm [21,22]. The commonly-applied path optimization methods include the shortest path search al- [23], the ant colony intelligent algorithm [24], the Dijkstra algorithm [25], the Floyd algorithm [26], etc. For example, Wu et al. [27] designed a new fuzzy scheduling optimization system based on the ant colony algorithm for multi-objective transportation paths. ...
Bulk materials are necessary for hydropower construction. The bulk materials transportation (BMT) scheme is a guiding document for material supply, and its selection has a significant influence on hydropower construction. Since the BMT problem includes transportation planning and scheme selection issues simultaneously, only a small number of studies have focused on it. This paper presents a theoretical two-stage decision-making method (TDM), which innovatively combines the path optimization method and the multi-criteria decision-making (MCDM) method to solve the BMT problem. In the first stage, a multi-source path optimization model is established to optimize the transportation network and obtain a set of alternatives from each supply point to the construction site. In the second stage, considering the factors of economy, risk and construction progress, the MCDM method is adopted to select the optimal scheme from the alternatives. In addition, web crawler technology is used to obtain the transportation network data from the public WebGIS automatically. Case results show that the TDM can effectively solve this problem, and its result keeps consistent with engineering practice; with the help of the web crawler, it can reduce the design task time from months to days. Therefore, the TDM based on WebGIS can benefit hydropower construction design efficiency.
... A* algorithm is good at solving the problem of the static path in the shortest distance and is different from the Dijkstra algorithm and Floyd algorithm, this algorithm combines advantages of breadth-first search (BFS) and Dijkstra algorithm [18]: in the heuristic search at the same time, enhance the efficiency of the algorithm can guarantee to find an optimal path (based on the evaluation function, such as the Manhattan distance, Euclidean distance), Floyd algorithm [19] using more scenes in robot path planning, game programming, satellite path search, and other fields. ...
... end if 18: end for 19: end for T in Algorithm 2 represents the query time window. Since DGPR is constantly iterating to calculate the capacity value of each region, the algorithm will re-read the road network data and sort the regions when the time reaches T. The value of T will be discussed in the experimental section. ...
Emergency path planning technology is one of the research hotspots of intelligent transportation systems. Due to the complexity of urban road networks and congested road conditions, emergency path planning is very difficult. Road congestion caused by urban emergencies directly affects the original road network structure. In this way, the static weight of the original road network is no longer suitable as the basis for path recommendation. To handle the dynamic situational road network, an equidistant grid emergency path planning framework will be designed. A novel situation grid road network model, based on situation information, is proposed and applied to an equidistant grid emergency path planning framework. A situational grid heuristic search will be proposed methodology based on this model, which can be used to detect the vehicles passing around the congestion area grid and the road to the destination in the shortest time. In the path planning methodology, a grid inspired search strategy based on quaternion function is included, which can make the algorithm converge to the target grid quickly. Three graph acceleration algorithms are proposed to improve the search efficiency of path planning algorithm. Finally, this paper will set up three experiments to verify our proposed method.
... If each edge in a graph G is assigned a numerical weight (which is usually taken to be positive integer), then G is called a weighted graph. A shortest path in a weighted graph is a path where the sum of the weights of edges is minimum [15]. A fuzzy weighted graph (network) in this research is graph (network) with fuzzy weights which are triangular fuzzy numbers. ...
Fuzzy graph became a nice tool for modeling and designing a network that contains indeterminacy. Public transportation has become a necessity in Bantul Regency because it is one of the regions that became popular in Yogyakarta Special Region Province (YSR), Indonesia. There are many tourism sectors in Bantul that became favourite destinations in recent years. However, we cannot obtain convenient public transportation that connects the favourite destinations in Bantul. Therefore, it is needed a bus rapid transit (BRT) in Bantul which will be called as “Trans Bantul”. The problem is how to determine optimal routes that connect public facilities in Bantul. In the real problem cases, a route between two places contains indeterminate parameters, such as distance, time, and cost. Hence, it is suitable to represent the bus stops and all possible roads in a fuzzy network, especially fuzzy weighted network. In this research, we use fuzzy shortest path approach to find optimal routes for public bus. We design an algorithm to determine optimal routes based on fuzzy shortest path algorithm. We construct a Matlab code according to a combination of Chuang-Kung and Yadav-Biswas algorithms. The weights on the network are the distances between two bus stops which are represented in triangular fuzzy numbers and we use the code to find the optimal routes. We have implemented the algorithm for route planning of the BRT “Trans Bantul” in Yogyakarta, Indonesia. The experimental results show that we can use three routes where the shortest distance in route 1 is 30.8 Km; the shortest distance in route 2 is 26.8 Km; and the shortest distance in route 3 is 20.8 Km. Further, the information of the bus routes is displayed in the Matlab GUI.
At present, the amount of data from users is increasing exponentially, and most of the data is stored in data centers distributed in different geographic locations. The cost of transferring large amounts of data across geographically distributed data centers can become prohibitive. Therefore, to shorten the data transmission time and reduce the cost of data transmission bandwidth and maintain the load balance of the geographically distributed cloud system, an optimal data placement strategy considering capacity limitation and load balancing in a geographically distributed cloud is proposed. Firstly, the capacity limitation, load balancing, and bandwidth cost of each cloud data center in the geographically distributed cloud are considered, and the data placement problem in the geographically distributed cloud is mathematically modeled. Secondly, the Floyd algorithm is used to model the cost of data transmission bandwidth and find the minimum transmission bandwidth cost. Finally, the Lagrangian relaxation method is used to obtain the optimal data placement scheme for the transmission time. To show the performance advantages of the proposed algorithm, comparative experiments are carried out. When the bandwidth is 15 Mbps, in terms of the Load Balancing Degree (LBD), the proposed algorithm is 40.3% higher than the Hash on average, 35.6% higher than the Closest on average, and 25.7% higher than the CRANE on average. Moreover, the experimental results show that the proposed algorithm can reduce the data transmission cost, and improve the load balancing in a geographically distributed cloud system.
