scholarly journals APLIKASI TRAVELLING SALESMAN PROBLEM PADA PENGEDROPAN BARANG DI ANJUNGAN MENGGUNAKAN METODE INSERTION

2021 ◽  
Vol 12 (2) ◽  
pp. 63
Author(s):  
Priska Sari Dewi ◽  
Triyani Triyani ◽  
Siti Rahmah Nurshiami
Keyword(s):  
Shortest Path ◽  
Travelling Salesman Problem ◽  
Travelling Salesman ◽  
Insertion Method

Travelling Salesman Problem (TSP) is a problem to find the shortest path a salesman visitS all the cities exactly once, and return to the starting city. In this reseacrh, the methods for TSP used are the nearest insertion method, the cheapest insertion method, and the farthest insertion method. With help the function of Software R to creat a minimum TSP Program from three insertion methods.The TSP results for same number of point using three insertion methods do not always have the same weight and route but depending on the data used.

scholarly journals Fixed Task Scheduling of Industrial Robot using Genetic Algorithm Based Travelling Salesman Problem

2020 ◽  
Vol 9 (5) ◽  
pp. 1771-1775
Keyword(s):  
Genetic Algorithm ◽  
Task Scheduling ◽  
Shortest Path ◽  
Completion Time ◽  
Travelling Salesman Problem ◽  
Industrial Robots ◽  
Scheduling Problem ◽  
Search Technique ◽  
Travelling Salesman ◽  
Algorithm Search

The task scheduling of any industrial robots is a prior requirement to effectively use the capability by obtaining shortest path with optimum completion time. In this article, we have presented Travelling Salesman Problem (TSP) with Genetic Algorithm (GA) search technique based task scheduling technique for obtaining optimum shortest path of the task.TSP finds an optimal solution to search for the shortest route by considering every location for completing the required tasks by setting up GA. This article embrace the adaption and implementation of the Genetic Algorithm search strategy for the task scheduling problem in the cooperative control of multiple resources for getting shortest path with minimize the completion time for two zone specific task allocation problem. It can be inferred from the simulation results that the Genetic Algorithm search technique can be considered as a viable solution for the task scheduling problem.

scholarly journals A New Approach Based on K-means Clustering and Shuffled Frog Leaping Algorithm to Solve Travelling Salesman Problem

2019 ◽  
Vol 2 (3) ◽  
pp. 446-453
Author(s):  
Murat Karakoyun
Keyword(s):  
Shortest Path ◽  
Travelling Salesman Problem ◽  
Experimental Results ◽  
Hard Problem ◽  
Shuffled Frog Leaping Algorithm ◽  
Travelling Salesman ◽  
New Approach ◽  
Starting Point ◽  
Np Hard Problem ◽  
Shuffled Frog Leaping

The Travelling Salesman Problem (TSP), which is a combinatorial NP-hard problem, aims to find the shortest possible path while visiting all cities (only once) in a given list and returns to the starting point. In this paper, an approach, which is based on k-means clustering and Shuffled Frog Leaping Algorithm (SFLA), is used to solve the TSP. The proposed approach consists of three parts: separate the cities into k clusters, find the shortest path for each cluster and merge the clusters. Experimental results have shown that the algorithm get better results as the number of cluster increase for problems that have a large number of cities.

PENGAPLIKASIAN ALGORITMA GENETIKA DALAM MENENTUKAN JALUR JALAN OPTIMAL WILAYAH KOTA PARIAMAN DENGAN LINTASAN TERPENDEK (SHORTEST PATH)

2017 ◽  
Vol 4 (1) ◽  
pp. 59
Author(s):  
Rida Fadila ◽  
Eka Sabna
Keyword(s):  
Shortest Path ◽  
Travelling Salesman Problem ◽  
Travelling Salesman

Algoritma Genetika adalah teknik pencarian dan optimasi yang terinspirasi oleh prinsip genetik dan seleksi alam (teori evolusi Darwin).Algoritma ini digunakan untuk mendapatkan solusi yang tepat untuk permasalahan optimasi dengan satu variabel atau multi variabel.                 Permasalahan Travelling Salesman Problem merupakan salah satu persoalan optimasi kombinatorial. TSP merupakan persoalan yang sulit bila dipandang dari sudut  komputasinya. Beberapa metode telah digunakan untuk memecahkan persoalan tersebut. Dan algoritma genetika merupakan solusi dalam menentukan perjalanan terpendek yang melalui kota lainnya hanya sekali dan kembali ke kota asal keberangkatan.                 Pada algoritma genetika, teknik pencarian dilakukan sekaligus atas sejumlah solusi yang dikenal dengan istilah populasi. Individu yang terdapat dalam satu populasi disebut dengan istilah kromosom. Algoritma genetika ini terdiri dari beberapa prosedur utama yaitu prosedur seleksi, crossover, mutasi dan elitisme. Algoritma genetika dirancang menjadi suatu program dengan menggunakan Matlab 7.9 untuk penyelesaian permasalahan tersebut.

The shortest path through many points

1959 ◽  
Vol 55 (4) ◽  
pp. 299-327 ◽  
Author(s):  
Jillian Beardwood ◽  
J. H. Halton ◽  
J. M. Hammersley
Keyword(s):  
Euclidean Space ◽  
Shortest Path ◽  
Travelling Salesman Problem ◽  
Dimensional Euclidean Space ◽  
Closed Path ◽  
Street Network ◽  
Plane Region ◽  
Travelling Salesman ◽  
Plateau’S Problem ◽  
Network Problem

ABSTRACTWe prove that the length of the shortest closed path throughnpoints in a bounded plane region of areavis ‘almost always’ asymptotically proportional to √(nv) for largen; and we extend this result to bounded Lebesgue sets ink–dimensional Euclidean space. The constants of proportionality depend only upon the dimensionality of the space, and are independent of the shape of the region. We give numerical bounds for these constants for various values ofk; and we estimate the constant in the particular casek= 2. The results are relevant to the travelling-salesman problem, Steiner's street network problem, and the Loberman—Weinberger wiring problem. They have possible generalizations in the direction of Plateau's problem and Douglas' problem.

scholarly journals Using genetic algorithm to solve multiple traveling salesman problem and considering Carbon emissions

2020 ◽  
Vol 13 (36) ◽  
pp. 3707-3715
Author(s):  
Chris Jojo Obi ◽  
Keyword(s):  
Genetic Algorithm ◽  
Traveling Salesman Problem ◽  
Carbon Emission ◽  
Travelling Salesman Problem ◽  
Time Windows ◽  
Traveling Salesman ◽  
Transport Cost ◽  
Travelling Salesman ◽  
Insertion Method ◽  
Multiple Travelling Salesman Problem

Objectives: The Multiple Travelling Salesman problem is a complex combinatorial optimization problem which is a variance of the Traveling Salesman Problem,where a lot of salesmen are utilized in the solution. In this work a cold chain logistics and route optimization model with minimum transport cost, carbon cost and Refrigeration cost are constructed. Methods: A genetic algorithm is then proposed to solve for the Multiple Travelling Salesman Problem with time windows while transport cost, carbon emission cost and refrigeration cost is minimized. Findings: It was observed that the algorithm evolved towards the direction of the optimal value of the fitness function. Novelty: There are a number of studies that considered tournament selection strategy but just a few have applied genetic algorithm considering insertion method to solve a Multiple Travelling salesman Problem. This study uses insertion method to obtain optimal solution. Also, the researcher considered time windows, transport cost, carbon emission cost and refrigeration cost. Keywords: Genetic algorithm method; cold-logistics; multiple travelling salesman problem

scholarly journals Tourist Route Optimization in the Context of Covid-19 Pandemic

2021 ◽  
Vol 13 (10) ◽  
pp. 5492
Author(s):  
Cristina Maria Păcurar ◽  
Ruxandra-Gabriela Albu ◽  
Victor Dan Păcurar
Keyword(s):  
Travelling Salesman Problem ◽  
Route Planning ◽  
Route Optimization ◽  
Travelling Salesman ◽  
Social Distancing ◽  
Tourist Destinations ◽  
Innovative Method ◽  
The Social ◽  
Immediate Response

The paper presents an innovative method for tourist route planning inside a destination. The necessity of reorganizing the tourist routes within a destination comes as an immediate response to the Covid-19 crisis. The implementation of the method inside tourist destinations can bring an important advantage in transforming a destination into a safer one in times of Covid-19 and post-Covid-19. The existing trend of shortening the tourist stay length has been accelerated while the epidemic became a pandemic. Moreover, the wariness for future pandemics has brought into spotlight the issue of overcrowded attractions inside a destination at certain moments. The method presented in this paper proposes a backtracking algorithm, more precisely an adaptation of the travelling salesman problem. The method presented is aimed to facilitate the navigation inside a destination and to revive certain less-visited sightseeing spots inside a destination while facilitating conformation with the social distancing measures imposed for Covid-19 control.

A column-and-row generation approach for the flying sidekick travelling salesman problem

2021 ◽  
Vol 124 ◽  
pp. 102913
Author(s):  
Maurizio Boccia ◽  
Adriano Masone ◽  
Antonio Sforza ◽  
Claudio Sterle
Keyword(s):  
Travelling Salesman Problem ◽  
Travelling Salesman
Sign in / Sign up

Export Citation Format

Share Document