Many studies have been performed since the introduction of GPS in Korea. As a result, positioning usingGNSS was fully proposed. On the other hand, most of these studies focused on accuracy but analytical studies on the GNSS status and the national GNSS infrastructure of Korea are lacking. In this study, the status of multi-constellation GNSS and National Geographic Information Institute's CORS (Continuous Operating Reference Station) were identified for the benefit and direction of GNSS infrastructure enhancement. As a result, it has beenoperating Multi-constellation GNSS, such as GPS, GLONASS, Galileo, COMPASS, and QZSS for surveying. In addition, improvement was presented by the number of satellites, precision, PDOP, etc. through the experiment aboutVRS and RTK using Multi-constellation GNSS. Upgrading the infrastructure for satellite surveying was identified as a priority consideration. In the future, if a Multi-constellation GNSS service is possible in VRS service, the satisfaction of public administration service will improve, which will contribute greatly to the advancement of a surveying infrastructure.

Analysis of Positioning Performance According to the Condition of Multi-constellation GNSS

This paper demonstrates that centralized economic load dispatch optimization is much more economical than independent optimization carried out by individual power generating companies. The algorithm applied here optimizes by balancing the generation power at the valve-point, then readjusting generation power by comparing incremental operating cost incurred by marginal increase in the generation power and decremental operating cost likewise incurred by marginal decrease in the generation power. Upon comparing 3 individual optimization cases of 10, 13, and 40 generators respectively with centralized optimization of 63 generators, centralized operation for economic load dispatch optimization has proven to maximize economic benefits by markedly reducing operation costs of individual optimization.

Economic Profit Analysis for Centralized Operation of Economic Load Dispatch Problem

/pdf/a-point-to-point-shortest-path-search-algorithm-in-an-1kduv1g0ct.pdf

A Point-to-Point Shortest Path Search Algorithm in an Undirected Graph Using Minimum Spanning Tree

This paper suggests an algorithm that can shorten the complexity of Dijkstra algorithm that is applied to the shortest path searching in real-time GPS Navigation System into an up-to-date O(n). Dijkstra algorithm manipulates the distance of the minimum length path by visiting all the nodes from the starting node. Hence, it has one disadvantage of not being able to provide the information on the shortest path every second, in a city that consists of sophisticated roads, since it has to execute number of node minus 1. The suggested algorithm, firstly, runs by means of organizing the set of out-neighbourhood nodes at each level of the tree, and root node for departure node. It also uses a method of manipulating the distance of the minimum path of all out-neighborhoods and interior of the out-neighborhoods. On applying the suggested algorithm to two sophisticated graphs consisted of bi-direction and uni-direction, we have succeeded to obtain the distance of the minimum length path, just as same as Dijkstra algorithm. In addition, it has an effect of shortening the time taken 4 times from number of node minus1 to number of level minus 1. The satisfaction of the drivers can be increased by providing the information on shortest path of detour, every second, when occurs any rush hour or any traffic congestion due to car accident, by applying this suggested algorithm to the real-time GPS system.

A Point-to-Point Shortest Path Algorithm Based on Level Node Selection

This paper proposes a simple linear function approximation method to solve an economic load dispatch problem with complex non-smooth generating cost function. This algorithm approximates a non-smooth power cost function to a linear approximate function and subsequently shuts down a generator with the highest operating cost and reduces the power of generator with more generating cost in order to balance the generating power and demands. When applied to the most prevalent benchmark economic load dispatch cases, the proposed algorithm is found to dramatically reduce the power cost than does heuristic algorithm. Moreover, it has successfully obtained results similar to those obtained through a quadratic approximate function method. Key Words : Economic load dispatch, Optimization, Shutdown, Smooth and non-smooth function, Function approximation * 정회원, 강릉원주대학교 과학기술대학 멀티미디어공학과접수일자 : 2013년 2월 11일, 수정완료 : 2014년 5월 3일게재확정일자 : 2014년 6월 13일Received: 11 February, 2014 / Revised: 3 May, 2014 /Accepted: 13 June, 2013

Optimization of Economic Load Dispatch Problem Using Linearly Approximated Smooth Fuel Cost Function

As the Transportation Simplex Method of the general transportation problem are inapplicable to the large-scale unbalanced transportation problem, a commercialized linear programming package remains as the only viable means. There is, however, no method made available to verify the optimality of solutions attained by the package. This paper therefore proposes a simple heuristic algorithm to the large-scale unbalanced transportation problem. From a given problem of supply and demand areas, the proposed algorithm determines the number of demands areas for each supply area and executes on the latter in the ascending order of each of their corresponding demand areas. Next, given a single corresponding demand area, it supplies the full demand volume and else, it supplies first to an area of minimum associated costs and subsequently to the rest so as to meet the demand to the fullest extent. This initial optimal value is then optimized through an adjustment process whereby costs are minimized as much as possible. When tested on the cost matrix, the proposed algorithm has obtained an optimal result improved from the commercial linear programming package by 8.9%.

Simple Algorithm for Large-scale Unbalanced Transportation Problem

This paper suggests a fast minimum spanning tree algorithm which simplify the original graph to 2-edge connected graph, and using the cycling property. Borůvka algorithm firstly gets the partial spanning tree using cycle property for one-edge connected graph that selects the only one minimum weighted edge  per vertex  . Additionally, that selects minimum weighted edge between partial spanning trees using cut property. Kruskal algorithm uses cut property for ascending ordered of all edges. Reverse-delete algorithm uses cycle property for descending ordered of all edges. Borůvka and Kruskal algorithms always perform  times for all edges. The proposed algorithm obtains 2-edge connected graph that selects 2 minimum weighted edges for each vertex firstly. Secondly, we use cycle property for 2-edges connected graph, and stop the algorithm until  For actual 10 benchmark data, The proposed algorithm can be get the minimum spanning trees. Also, this algorithm reduces 60% of the trial number than Borůvka, Kruskal and Reverse-delete algorithms.

http://koreascience.or.kr:80/article/JAKO201426636276418.pdf

Proposal of Minimum Spanning Tree Algorithm using 2-Edges Connected Grap

In the absence of a deterministic algorithm for economic load dispatch optimization problem (ELDOP), existing algorithms proposed as solutions are inevitably non-deterministic heuristic algorithms. This paper, therefore, proposes a balance-and-swap algorithm to solve an ELDOP. Firstly, it balances the initial value to     by subsequently reducing power generation for each adult-step and baby-step and selects the minimum cost-generating method. Subsequently, it selects afresh the minimum cost-generating method after an optimization of the previously selected value with adult-step baby-step swap and giant-step swap methods. Finally, we perform the   ± swap. When applied to the 3 most prevalently used economic load dispatch problem data, the proposed algorithm has obtained improved results for two and a result identical to the existing one for the rest. This algorithm thus could be applied to ELDOP for it has proven to consistently yield identical results and to be applicable to all types of data.

Sang-Un Lee

Papers

A Point-to-Point Shortest Path Algorithm Based on Level Node Selection

Optimization of Economic Load Dispatch Problem Using Linearly Approximated Smooth Fuel Cost Function

Simple Algorithm for Large-scale Unbalanced Transportation Problem

Proposal of Minimum Spanning Tree Algorithm using 2-Edges Connected Grap

Optimization Algorithm for Economic Load Dispatch Problem Using Balance and Swap Method