| Abstrakt: |
The shortest path solver is a program that aims to find the route with the lowest total edge weight between two points in a graph. Commonly used algorithms include Dijkstra for graphs with non-negative edge weights, Bellman-Ford for graphs with negative edge weights, and Floyd-Warshall for finding the shortest path between all point pairs. Its application is wide, ranging from navigation systems, computer networks, to logistics and games. The process of using it involves creating a graph model, selecting the appropriate algorithm, running a solver, and analyzing the results. A practical example shows how the Dijkstra algorithm can be used to determine the shortest route between cities in a road network, with effective and accurate results. The shortest path solver proves to be a versatile and essential tool for solving a wide range of problems in a variety of fields. This research uses quantitative methods with an experimental approach to test the effectiveness and efficiency of using the shortest path method with Solver Excel in optimizing goods delivery routes. The research object is the delivery route from the warehouse to several delivery destinations, with a sample of 10 routes that are most frequently used and have the highest delivery volume. Primary data was obtained through direct observation and interviews with company logistics managers. The results of this study show that the use of shortest path method with Excel Solver is effective in optimising the route of delivery of goods, reducing the cost and time of delivery by 15% and 10%. Although there are limitations for large networks, this tool remains useful and flexible. This implementation can be a reference for other companies to improve their logistics efficiency. [ABSTRACT FROM AUTHOR] |
