scholarly journals PENENTUAN LINTASAN TERPENDEK DARI FMIPA KE REKTORAT DAN FAKULTAS LAIN DI UNSRAT MANADO MENGGUNAKAN ALGORITMA DJIKSTRA

2011 ◽  
Vol 11 (1) ◽  
pp. 73
Author(s):  
Deiby T. Salaki

Universitas Sam Ratulangi Manado adalah salah satu perguruan tinggi di Sulawesi Utara yang terdiri atas 11 fakultas dan satu gedung rektorat. Setiap fakultas dan rektorat terhubung dengan fasilitas jalan raya. Secara matematis kondisi seperti ini dapat direpresentasikan sebagai sebuah graf yang bisa diterapkan untuk mencari lintasan terpendek. Pada penelitian ini akan dicari lintasan terpendek dari FMIPA ke rektorat dan fakultas lainnya. Dengan menggunakan algoritma Djikstra, lintasan terpendek dari FMIPA diperoleh dengan memilih minimum lokal atau akses dengan jarak terdekat dari setiap lokasi yang kemudian digabungkan menjadi sebuah kumpulan lintasan dari satu lokasi ke lokasi lainnya dengan jarak terpendek. DETERMINATION OF SHORTEST PATH FROM FMIPA TO RECTORATE AND OTHER FACULTIES AT SAM RATULANGI UNIVERSITY USING DJIKSTRA ALGORITHMABSTRACTSam Ratulangi University is one of the colleges in North Sulawesi consisting of 11 faculties and one rectorate building. Every faculty and rectorate connected by highway facilities. Mathemathically this condition can be represented as an undirected weighted graph that can be applied to find the shortest path. By using the Djikstra algorithm, the shortest paths are obtained by setting the FMIPA as the initial vertex and then select the local minimum or access to the closest distance from each location, then combined the collection of path from one location to another with the shortest distance.

2000 ◽  
Vol 10 (01) ◽  
pp. 51-58 ◽  
Author(s):  
SVEN VENEMA ◽  
HONG SHEN ◽  
FRANCIS SURAWEERA

For a weighted, undirected graph G=(V, E) where |V|=n and |E|=m, we examine the single most vital edge with respect to all-pairs shortest paths (APSP) under two different measurements. The first measurement considers only the impact of the removal of a single edge from the APSP on the shortest distance between each vertex pair. The second considers the total weight of all the edges which make up the APSP, that is, calculate the sum of the distance between each vertex pair after the deletion of any edge belonging to a shortest path. We give a sequential algorithm for this problem, and show how to obtain an NC algorithm running in O( log n) time using mn2 processors and O(mn2) space on the MINIMUM CRCW PRAM. Given the shortest distance between each pair of vertices u and v, the diameter of the graph is defined as the longest of these distances. The Most vital edge with respect to the diameter is the edge lying on such a u–v shortest path which when removed causes the greatest increase in the diameter. We show how to modify the above algorithm to solve this problem using the same time and number of processors. Both algorithms compare favourably with the straightforward solution which simply recalculates the all pairs shortest path information.


2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Bingwu Zhang ◽  
Xiucui Guan ◽  
Chunyuan He ◽  
Shuguo Wang

In a shortest path improvement problem under unit Hamming distance (denoted by SPIUH), an edge weighted graph with a set of source-terminal pairs is given; we need to modify the lengths of edges by a minimum cost under unit Hamming distance such that the modified distances of the shortest paths are upper bounded by given values. The SPIUH problem on arborescent network is formulated as a 0-1 integer programming model. Some strongly polynomial time algorithms are designed for the problems on some special arborescent networks. Firstly, two greedy algorithms are proposed for problems on chain networks and special star-tree networks, respectively. Secondly, a strongly polynomial time algorithm is presented for the problem with a single source and constrained paths. Finally, a heuristic algorithm and its computational experiments are given for the SPIUH problem on general graphs.


2021 ◽  
Vol 82 (1-2) ◽  
Author(s):  
Lena Collienne ◽  
Alex Gavryushkin

AbstractMany popular algorithms for searching the space of leaf-labelled (phylogenetic) trees are based on tree rearrangement operations. Under any such operation, the problem is reduced to searching a graph where vertices are trees and (undirected) edges are given by pairs of trees connected by one rearrangement operation (sometimes called a move). Most popular are the classical nearest neighbour interchange, subtree prune and regraft, and tree bisection and reconnection moves. The problem of computing distances, however, is $${\mathbf {N}}{\mathbf {P}}$$ N P -hard in each of these graphs, making tree inference and comparison algorithms challenging to design in practice. Although anked phylogenetic trees are one of the central objects of interest in applications such as cancer research, immunology, and epidemiology, the computational complexity of the shortest path problem for these trees remained unsolved for decades. In this paper, we settle this problem for the ranked nearest neighbour interchange operation by establishing that the complexity depends on the weight difference between the two types of tree rearrangements (rank moves and edge moves), and varies from quadratic, which is the lowest possible complexity for this problem, to $${\mathbf {N}}{\mathbf {P}}$$ N P -hard, which is the highest. In particular, our result provides the first example of a phylogenetic tree rearrangement operation for which shortest paths, and hence the distance, can be computed efficiently. Specifically, our algorithm scales to trees with tens of thousands of leaves (and likely hundreds of thousands if implemented efficiently).


Algorithms ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 21
Author(s):  
Christoph Hansknecht ◽  
Imke Joormann ◽  
Sebastian Stiller

The time-dependent traveling salesman problem (TDTSP) asks for a shortest Hamiltonian tour in a directed graph where (asymmetric) arc-costs depend on the time the arc is entered. With traffic data abundantly available, methods to optimize routes with respect to time-dependent travel times are widely desired. This holds in particular for the traveling salesman problem, which is a corner stone of logistic planning. In this paper, we devise column-generation-based IP methods to solve the TDTSP in full generality, both for arc- and path-based formulations. The algorithmic key is a time-dependent shortest path problem, which arises from the pricing problem of the column generation and is of independent interest—namely, to find paths in a time-expanded graph that are acyclic in the underlying (non-expanded) graph. As this problem is computationally too costly, we price over the set of paths that contain no cycles of length k. In addition, we devise—tailored for the TDTSP—several families of valid inequalities, primal heuristics, a propagation method, and a branching rule. Combining these with the time-dependent shortest path pricing we provide—to our knowledge—the first elaborate method to solve the TDTSP in general and with fully general time-dependence. We also provide for results on complexity and approximability of the TDTSP. In computational experiments on randomly generated instances, we are able to solve the large majority of small instances (20 nodes) to optimality, while closing about two thirds of the remaining gap of the large instances (40 nodes) after one hour of computation.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Silvia Zaoli ◽  
Piero Mazzarisi ◽  
Fabrizio Lillo

AbstractBetweenness centrality quantifies the importance of a vertex for the information flow in a network. The standard betweenness centrality applies to static single-layer networks, but many real world networks are both dynamic and made of several layers. We propose a definition of betweenness centrality for temporal multiplexes. This definition accounts for the topological and temporal structure and for the duration of paths in the determination of the shortest paths. We propose an algorithm to compute the new metric using a mapping to a static graph. We apply the metric to a dataset of $$\sim 20$$ ∼ 20 k European flights and compare the results with those obtained with static or single-layer metrics. The differences in the airports rankings highlight the importance of considering the temporal multiplex structure and an appropriate distance metric.


2019 ◽  
Author(s):  
Marcelo Benedito ◽  
Lehilton Pedrosa ◽  
Hugo Rosado

In the Cable-Trench Problem (CTP), the objective is to find a rooted spanning tree of a weighted graph that minimizes the length of the tree, scaled by a non-negative factor , plus the sum of all shortest-path lengths from the root, scaled by another non-negative factor. This is an intermediate optimization problem between the Single-Destination Shortest Path Problem and the Minimum Spanning Tree Problem. In this extended abstract, we consider the Generalized CTP (GCTP), in which some vertices need not be connected to the root, but may serve as cost-saving merging points; this variant also generalizes the Steiner Tree Problem. We present an 8.599-approximation algorithm for GCTP. Before this paper, no constant approximation for the standard CTP was known.


2019 ◽  
Vol 10 (1) ◽  
pp. 4780-4785

Canary (Canarium indicum L.) is an indigenous plant of Indonesia, which mainly grows in the eastern part of Indonesia, especially in the Maluku, North Sulawesi, and Seram islands. We believe that no scientific reports have been conducted about L-tryptophan content in Canarium indicum. Therefore, this study was conducted to determine the presence and quantitate the aromatic amino acid (L-tryptophan) in the canary protein hydrolysate by the spectrofluorometric method. The protein hydrolysate was prepared by two hydrolysis methods, enzymatic and alkaline hydrolysis. L-tryptophan can be differentiated from tyrosine directly without using any reagent by excitation of the sample at 295 nm in order to avoid tyrosine emission. The equation of calibration curve correlation using standard in the range 0.5-5 ppm was y = 6632.3x - 845.42 and correlation coefficient of 0.9997, while the coefficient of variance in linear regression was 1.29%. The detection limit and quantification limit obtained were 0.116 ppm and 0.35 ppm respectively. The recoveries of the accuracy test were obtained in the range of 95-96%. The relative standard deviation of intra-assay precision tests were obtained in the range of 0.5-1.8%, while the intermediate precision in the range of 2.18-3.74%. L-tryptophan was detected in all samples (papain, pepsin, and alkaline hydrolysate), with concentrations 5.6, 5 and 1.53 mg/100mg of protein respectively. The used fluorometric method complied with the validation requirements and can be used to analyze L-tryptophan in samples containing tyrosine without overlapping of spectra and without the use of any specific reagent.


2019 ◽  
Author(s):  
Nate Wessel ◽  
Steven Farber

Estimates of travel time by public transit often rely on the calculation of a shortest-path between two points for a given departure time. Such shortest-paths are time-dependent and not always stable from one moment to the next. Given that actual transit passengers necessarily have imperfect information about the system, their route selection strategies are heuristic and cannot be expected to achieve optimal travel times for all possible departures. Thus an algorithm that returns optimal travel times at all moments will tend to underestimate real travel times all else being equal. While several researchers have noted this issue none have yet measured the extent of the problem. This study observes and measures this effect by contrasting two alternative heuristic routing strategies to a standard shortest-path calculation. The Toronto Transit Commission is used as a case study and we model actual transit operations for the agency over the course of a normal week with archived AVL data transformed into a retrospective GTFS dataset. Travel times are estimated using two alternative route-choice assumptions: 1) habitual selection of the itinerary with the best average travel time and 2) dynamic choice of the next-departing route in a predefined choice set. It is shown that most trips present passengers with a complex choice among competing itineraries and that the choice of itinerary at any given moment of departure may entail substantial travel time risk relative to the optimal outcome. In the context of accessibility modelling, where travel times are typically considered as a distribution, the optimal path method is observed in aggregate to underestimate travel time by about 3-4 minutes at the median and 6-7 minutes at the \nth{90} percentile for a typical trip.


Author(s):  
A. A. Heidari ◽  
M. R. Delavar

In realistic network analysis, there are several uncertainties in the measurements and computation of the arcs and vertices. These uncertainties should also be considered in realizing the shortest path problem (SPP) due to the inherent fuzziness in the body of expert's knowledge. In this paper, we investigated the SPP under uncertainty to evaluate our modified genetic strategy. We improved the performance of genetic algorithm (GA) to investigate a class of shortest path problems on networks with vague arc weights. The solutions of the uncertain SPP with considering fuzzy path lengths are examined and compared in detail. As a robust metaheuristic, GA algorithm is modified and evaluated to tackle the fuzzy SPP (FSPP) with uncertain arcs. For this purpose, first, a dynamic operation is implemented to enrich the exploration/exploitation patterns of the conventional procedure and mitigate the premature convergence of GA technique. Then, the modified GA (MGA) strategy is used to resolve the FSPP. The attained results of the proposed strategy are compared to those of GA with regard to the cost, quality of paths and CPU times. Numerical instances are provided to demonstrate the success of the proposed MGA-FSPP strategy in comparison with GA. The simulations affirm that not only the proposed technique can outperform GA, but also the qualities of the paths are effectively improved. The results clarify that the competence of the proposed GA is preferred in view of quality quantities. The results also demonstrate that the proposed method can efficiently be utilized to handle FSPP in uncertain networks.


d'CARTESIAN ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 1
Author(s):  
Ladi Beatriex Deeng ◽  
Hanny A H Komalig ◽  
John S Kekenusa

LADI BEATRIEX DEENG. Determination of Utilization and Management Status of Bonito (Auxis Rochei) Caught in South Bolaang-Mongondow and East Bolaang-Mongondow Waters of North Sulawesi. Supervised by Mr. JOHN S. KEKENUSA as main supervisor, and Mr. HANNY A. H. KOMALIG as co-supervisor.Bonito (Auxis rochei), needs to be managed properly because even though it is a renewable biological resource, it can experience overfishing, depletion or extinction. One way to approach the management of fish resources is by modeling. The analysis was carried out aiming to determine the status of utilization and management of bonito and maximum sustainable yield (MSY) using the Surplus Production Model. Data on catching and efforts to catch bonito is collected from the Marine and Fisheries Service of South Bolaang-Mongondow Regency and East Bolaang-Mongondow of North Sulawesi. The surplus production model that can be used to determine the catch of bonito is the Schaefer model. The maximum sustainable catch of bonito is 869.556 tons per year, obtained at the level of catching effort of 933 trips. For 2017 the level of utilization is 64.95 % so that production can still be increased, with a level of effort of 73.74 % indicating the level of effort that is not optimal and can still be increased. Keywords : Bonito, Surplus Production Model, South Bolaang-Mongondow and   East Bolaang-Mongondow Regency


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