Shortest Route Application via Dynamic Programming in the Transportation Networks

2021 ◽  
pp. 362-371
Author(s):  
Arzu Eren Şenaras ◽  
Şahin İnanç ◽  
Hayrettin Kemal Sezen ◽  
Onur Mesut Şenaras
Keyword(s):  
Dynamic Programming ◽  
Shortest Path ◽  
Dynamic Programming Method ◽  
Programming Approach ◽  
Dynamic Programming Approach ◽  
Transportation Sector ◽  
Shortest Route ◽  
Starting Point ◽  
Visual Basic Application ◽  
Destination Point

The purpose of this study is to develop an application for finding the shortest path in the transportation sector. The application was developed using the dynamic programming method in MS Excel Visual Basic application. These types of problems are also called stagecoach problems. The purpose of the problem is finding the shortest path between the starting point (node) and the destination point. Values are related to the roads in the network to specify the distance between two nodes. In case of a small number of nodes (activities), a solution can be reached by evaluating all options. But the number of possible options to be scanned for real problems is quite large. In such cases, a suitable method is needed for the solution. It can produce effective solutions with the dynamic programming approach.

scholarly journals A Compromise Decision Support Multi Objective Travelling Salesman Problem

2019 ◽  
Vol 8 (4) ◽  
pp. 10259-10262
Keyword(s):  
Dynamic Programming ◽  
Decision Support ◽  
State Space ◽  
Travelling Salesman Problem ◽  
Optimal Path ◽  
Programming Approach ◽  
Travelling Salesman ◽  
Multi Objective ◽  
Dynamic Programming Approach ◽  
Shortest Route

The multi objective travelling salesman problem simultaneously optimizes several objectives. It is also called as shortest cyclic route model with multiple objectives provides the shortest route. In this article, the compromised decision support solutions are processed for a multi objective travelling salesman problem. The dynamic programming approach for optimal path with state space tree is used to get the shortest route for the objectives. Based on decision maker's preference, the compromised solution for the multi objective travelling salesman problem is obtained. The proposed methodology is very simple and easy way to get the shortest route which is illustrated with an example.

scholarly journals AN OPTIMAL CONSUMPTION AND INVESTMENT PROBLEM WITH QUADRATIC UTILITY AND SUBSISTENCE CONSUMPTION CONSTRAINTS: A DYNAMIC PROGRAMMING APPROACH

2018 ◽  
Vol 23 (4) ◽  
pp. 627-628 ◽  
Author(s):  
Yong Hyun Shin ◽  
Jung Lim Koo ◽  
Kum Hwan Roh
Keyword(s):  
Dynamic Programming ◽  
Optimization Problem ◽  
Sufficient Conditions ◽  
Dynamic Programming Method ◽  
Programming Approach ◽  
Optimal Consumption ◽  
Dynamic Programming Approach ◽  
Investment Problem ◽  
Optimal Consumption And Investment ◽  
Consumption Constraints

In this paper, we analyze the optimal consumption and investment problem of an agent who has a quadratic-type utility function and faces a subsistence consumption constraint. We use the dynamic programming method to solve the optimization problem in continuous-time. We further provide the sufficient conditions for the optimization problem to be well-defined.

scholarly journals A Note on Multimachine Scheduling with Weighted Early/Late Work Criteria and Common Due Date

2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Kerang Cao ◽  
Xin Chen ◽  
Kwang-nam Choi ◽  
Yage Liang ◽  
Qian Miao ◽  
...  
Keyword(s):  
Dynamic Programming ◽  
Flow Shop ◽  
Dynamic Programming Method ◽  
Programming Approach ◽  
Due Date ◽  
Enumeration Algorithm ◽  
Late Work ◽  
Common Due Date ◽  
Dynamic Programming Approach ◽  
Early Late

In this note, we revisit two types of scheduling problem with weighted early/late work criteria and a common due date. For parallel identical machines environment, we present a dynamic programming approach running in pseudopolynomial time, to classify the considered problem into the set of binary NP-hard. We also propose an enumeration algorithm for comparison. For two-machine flow shop systems, we focus on a previous dynamic programming method, but with a more precise analysis, to improve the practical performance during its execution. For each model, we verify our studies through computational experiments, in which we show the advantages of our techniques, respectively.

The Map-Based Shortest Route Selection by Using Ant Colony Optimization Algorithm

2018 ◽  
Vol 1 (1) ◽  
pp. 15
Author(s):  
Achmad Fanany Onnilita Gaffar ◽  
Agusma Wajiansyah ◽  
Supriadi Supriadi
Keyword(s):  
Ant Colony Optimization ◽  
Shortest Path ◽  
Optimization Algorithm ◽  
Optimization Problems ◽  
Google Earth ◽  
Ant Colony ◽  
Food Sources ◽  
Shortest Route ◽  
Study Results ◽  
Destination Point

The shortest path problem is one of the optimization problems where the optimization value is a distance. In general, solving the problem of the shortest route search can be done using two methods, namely conventional methods and heuristic methods. The Ant Colony Optimization (ACO) is the one of the optimization algorithm based on heuristic method. ACO is adopted from the behavior of ant colonies which naturally able to find the shortest route on the way from the nest to the food sources. In this study, ACO is used to determine the shortest route from Bumi Senyiur Hotel (origin point) to East Kalimantan Governor's Office (destination point). The selection of the origin and destination points is based on a large number of possible major roads connecting the two points. The data source used is the base map of Samarinda City which is cropped on certain coordinates by using Google Earth app which covers the origin and destination points selected. The data pre-processing is performed on the base map image of the acquisition results to obtain its numerical data. ACO is implemented on the data to obtain the shortest path from the origin and destination point that has been determined. From the study results obtained that the number of ants that have been used has an effect on the increase of possible solutions to optimal. The number of tours effect on the number of pheromones that are left on each edge passed ant. With the global pheromone update on each tour then there is a possibility that the path that has passed the ant will run out of pheromone at the end of the tour. This causes the possibility of inconsistent results when using the number of ants smaller than the number of tours.

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