M. Yamuna* et al. International Journal of Pharmacy & Technology

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1 ISSN: X CODEN: IJPTFI Available Online through Research Article AMULANCE SERVICE USING MODIFIED DIJKSTRA S ALGORITHM Chhandak agchi, Khushbu Chopra, M. Yamuna* VIT University, Vellore, Tamil Nadu, India. myamuna@vit.ac.in Received on Accepted on Abstract Ambulance service is one of the most critical services to be operated anytime. An ambulance reaching a patient at the right time and reaching a hospital at the minimum possible time is very crucial as it is the time that decides the life of a person. In this paper we propose a method of developing a predefined data about the distance to reach an ambulance service using Dijkstra s algorithm, which will aid in picking a wise nearest service. Keywords: Ambulance, shortest path, Dijkstra s algorithm. Introduction There are many shortest path algorithms available. ut the most used one is Dijkstra s Shortest Path Algorithm. It is easy to be implemented. This algorithm has been used either directly or with some modifications. In [ 1 ] Ni Kai et al discussed the shortest path analysis based on Dijkstra s algorithm and implemented a emergency response system based on GIS, which can be widely used in all sorts of services that in any way handle sources and consequences of emergencies. In [ 2 ] among the several models of routes selecting in practice and, Ivan eker et al investigated the implementation of one of them the shortest path algorithms for forklifts routing optimization. y calculating the optimal route for forklifts, transportation routes are shortened and work in the warehouses is reduced. In [ 3 ] Liu XiaoYan et al used heap sort to sort unlabelled nodes in geography network to improve the efficiency of Dijkstra algorithm. They provided separate solutions of path optimization based on Dijkstra algorithm in logistics distribution lines with barriers and no barriers. They proposed modified Dijkstra algorithm given vehicle, weather and other factors. In [ 4 ] Charika Jain studied how to select a path with the minimum cost in terms of expected endtoend delay in a network. Different from the previous efforts, the new endtoend delay takes the queuing delay and transmission IJPT Sep2016 Vol. 8 Issue No Page 17627

2 delay into account with propagation delay, since the endtoend delay consist of not only the propagation delay but also the transmission delay and queuing delay in buffer. In [ 5 ] FAN Jun et al improved the classical Dijkstra algorithm by means of two aspects in this paper, and realizes the shortest (safest) routing in the actual road network safety management. A review reveals that Dijkstra s algorithm can be used for various cases. In this paper we provide a method of efficient ambulance management using this algorithm. Preliminary Note In this section we provide details in the original Dijkstra s algorithm, and the improvised version of the same, that is to be used in the proposed method. Conventional Algorithm Dijkstra's algorithm is an algorithm for finding the shortest paths between nodes in a graph. Stepwise approach for the algorithm is 1. Assign to every node a tentative distance value: set it to zero for our initial node and to infinity for all other nodes. 2. Set the initial node as current. Mark all other nodes unvisited. Create a set of all the unvisited nodes called the unvisited set. 3. For the current node, consider all of its unvisited neighbors and calculate their tentative distances. Compare the newly calculated tentative distance to the current assigned value and assign the smaller one. For example, if the current node A is marked with a distance of 6, and the edge connecting it with a neighbor has length 2, then the distance to (through A) will be = 8. If was previously marked with a distance greater than 8 then change it to 8. Otherwise, keep the current value. 4. When we are done considering all of the neighbors of the current node, mark the current node as visited and remove it from the unvisited set. A visited node will never be checked again. 5. If the destination node has been marked visited (when planning a route between two specific nodes) or if the smallest tentative distance among the nodes in the unvisited set is infinity (when planning a complete traversal; occurs when there is no connection between the initial node and remaining unvisited nodes), then stop. The algorithm has finished. 6. Otherwise, select the unvisited node that is marked with the smallest tentative distance, set it as the new "current node", and go back to step 3. IJPT Sep2016 Vol. 8 Issue No Page 17628

3 Drawbacks of the Conventional Algorithm M. Yamuna* et al. International Journal of Pharmacy & Technology The conventional Dijkstra s algorithm has certain drawbacks such as lots of redundancy of space and time. The algorithm based on the storage of data structure stores network information with appropriate data structure before carrying out the shortest path search. The number of elements in correlation matrix expands as geometric series with the increasing of nodes/vertices, which brings a serious waste of resource space and lots of useless cycle. Thus search efficiency is seriously reduced. According to the algorithm, length of the shortest path from v s to any point v p in set of (V S), and satisfy dp as follow d p = min[d i,d k +l kp ],v p V S, v k S, where, l kp is the direct distance from point k to point j. Improvised Version In order to reduce the search range, the proposed improved algorithm based on the search strategy introduces constraint functions r(n) for each searching node in state space. So the core formula of the improved shortest algorithm is defined as follows [6]. D( n ) = d( n ) + r ( n ), π/2 θ n π/2, where, r(n) = ω*cos(θ n ), d(n) denotes the weight value of shortest path from the starting point to the current node n. r(n) is constraint function, ω is a weighted value denoting the impact factor, θn is the angle between the vector that consists of nodes from starting point to current node and the vector that consists of nodes from starting point to the end point. ecause of the limitation of θn, the search range of is reduced and the search efficiency is improved. Proposed Method In the proposed method we use the improvised method to provide a method of ambulance service. When there is a request for ambulance service, then the main aim is to reach the destination as early as possible. asically we need to decide the shortest path from source to destination. Here the source is the availability of the ambulance. When there is a request, there may or may not be an ambulance available. If ambulance is not available nearby, then we need to find the next nearest. We try to devise a method using improved Dijikstra, s algorithm, which we believe will improve the efficiency of ambulance service. We form a graph with vertices as the towns and edges as the roads connecting them. As a sample for this we choose Vellore district and proceed with the proposed method with illustration. The map of Vellore district is seen in Snapshot 1[7]. IJPT Sep2016 Vol. 8 Issue No Page 17629

4 Snapshot 1 All the towns of Vellore district are connected via major roads. This forms a graph with the towns as the vertices and roads as the edges. The district is further divided into four zones on the basis of proximity. There is at least one road that joins these zones. On removal of these connecting roads, it leads to four edgedisjoint graph components. An adjacency matrix is created by calculating distance between each town. The required order of the matrix is 47 x 47. When an ambulance request is created, a shortest path needs to be calculated between the source and the destination with respect to the ambulance. This is done by using improved version of Dijkstra s algorithm. We associate a counter with each zone that stores the number of ambulance in that zone. At the time of catering an ambulance request, initially it check the counter of that particular zone. If the value is nonzero, algorithm is applied to that zone. Otherwise, the algorithm is applied in the nearby zone, whose counter value is nonzero. When a shortest path is traced from source to destination, distance is calculated. A message is displayed specifying the ambulance details and the time required to reach the destination. Fig. 1 IJPT Sep2016 Vol. 8 Issue No Page 17630

5 As a sample we have picked a small situation with 10 vertices as seen in Fig. 1. Here the blue color vertex denotes the place of request of ambulance service. The other vertices denote places where ambulance service is likely to be available ( representing hospitals available in this area ). Dijkstra s Algorithm Here, we see that vertex 0 is the point from where the request for an ambulance has been made. The vertices A,, C, D, E, F, G, H and I are hospitals or centers with ambulances. Table 1 presents the shortest path using the conventional Dijksra s algorithm. 0 A C D E F G H I A C D C E C 150 I C E 1750 F 150 F C E 1740 F 150 G C E 1740 F 150 H C E 1740 F 1970 G 150 Table 1 Dijkstra s Algorithm As seen in the table the distance to reach H from vertex 0 is 1970 and the path can be determined by backtracking, that is H is reached from G, G from F, F from I, I from E, E from D, D from C, C from, from A and A to 0. Similarly, the distances for the other nearby services and the shortest route can also be calculated from the table. Improvised Dijkstra s Algorithm Table 2 presents the result for the same situation using improvised algorithm. ecause of the limitation of θn in the improvised version of the Dijkstra s algorithm, the search range of is reduced and the search efficiency is improved. When d(n) is large, in order to make sure that the constraint functions r(n) is not much less than d(n) in searching the shortest path, the impact factor should be set to a large value. ecause cosθn belongs to [1,1]. When r(n) is far more less than d(n) or r(n) is equal to 0, there is no constraint condition, and then the improved algorithm becomes a IJPT Sep2016 Vol. 8 Issue No Page 17631

6 conventional Dijkstra algorithm. Therefore, to avoid falling into endless loop by removing too many relevant nodes, r(n) should not be set to a too small value and the constraint value of current node should not be overestimated. 0 A C D E F G H I A C D E F G H G 245 I G 245 Table 2 Modified Dijkstra s Algorithm As can be seen from the table while backtracking we can use the suffix attached along with the values. The shortest path from 0 to I can be estimated looking from the last row. I to D (from the suffix), then D to C (from row D and suffix C), C to 0. Conclusion In this paper we have tried to provide a method for quick ambulance service using modified Dijkstra s algorithm. This method provides a predefined set of data about the ambulance services available nearby and the shortest route to IJPT Sep2016 Vol. 8 Issue No Page 17632

7 reach them. So in case of emergency one shall be able to decide which ambulance service would be best at the time of need. In case the nearest option is not available then one shall be able to decide the next nearest and so on. The proposed method will serve as a method to develop set of predefined data which can be used as a database to decide and approach ambulance services in case of emergency. References 1. Ni Kai, Zhang Yaoting, Ma Yuepeng, Shortest Path Analysis ased on Dijkstra's Algorithm in Emergency Response System, TELKOMNIKA Indonesian Journal of Electrical Engineering, Vol.12, No.5, May 2014, pp ~ Liu XiaoYan, Chen YanLi, Application of Dijkstra Algorithm in Logistics. 3. Ivan eker, Vesna Jevtić, Dalibor Dobrilović, Shortestpath algorithms as a tools for inner transportation Optimization, International Journal of Industrial Engineering and Management (IJIEM), Vol.3 No 1, 2012, pp Distribution Lines, Proceedings of the Third International Symposium on Computer Science and Computational Technology(ISCSCT 10) Jiaozuo, P. R. China, 1415,August 2010, pp Charika Jain, Jitendra Kumawat, Processing Delay Consideration in Dijkstra s Algorithm, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 3, Issue 8, August 2013, Yizhen Huang, Qingming Yi, Min Shi, An Improved Dijkstra Shortest Path Algorithm, Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013) Corresponding Author M. Yamuna*, myamuna@vit.ac.in IJPT Sep2016 Vol. 8 Issue No Page 17633