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.

Recombination Operators in Permutation-Based Evolutionary Algorithms for the Travelling Salesman Problem

2012 ◽  
pp. 268-285
Author(s):  
Camelia Chira ◽  
Anca Gog
Keyword(s):  
Genetic Algorithms ◽  
Optimization Problems ◽  
Travelling Salesman Problem ◽  
Genetic Material ◽  
Hard Problem ◽  
Travelling Salesman ◽  
Routing And Scheduling ◽  
Np Hard Problem ◽  
Account Information ◽  
Ant Colony Systems

The Travelling Salesman Problem (TSP) is one of the most widely studied optimization problems due to its many applications in domains such as logistics, planning, routing, and scheduling. Approximation algorithms to address this NP-hard problem include genetic algorithms, ant colony systems, and simulated annealing. This chapter concentrates on the evolutionary approaches to TSP based on permutation encoded individuals. A comparative analysis of several recombination operators is presented based on computational experiments for TSP instances and a generalized version of TSP. Numerical results emphasize a good performance of two proposed crossover schemes: best-worst recombination and best order recombination which take into account information from the global best and/or worst individuals besides the genetic material from parents.

scholarly journals Bee-Inspired Algorithms Applied to Vehicle Routing Problems: A Survey and a Proposal

2017 ◽  
Vol 2017 ◽  
pp. 1-20 ◽  
Author(s):  
Thiago A. S. Masutti ◽  
Leandro N. de Castro
Keyword(s):  
Vehicle Routing ◽  
Collective Intelligence ◽  
Travelling Salesman Problem ◽  
Optimal Solution ◽  
Vehicle Routing Problems ◽  
Open Problems ◽  
Chip Design ◽  
Routing Problems ◽  
New Approach ◽  
Np Hard Problem

Vehicle routing problems constitute a class of combinatorial optimization tasks that search for optimal routes (e.g., minimal cost routes) for one or more vehicles to attend a set of nodes (e.g., cities or customers). Finding the optimal solution to vehicle routing tasks is an NP-hard problem, meaning that the size of problems that can be solved by exhaustive search is limited. From a practical perspective, this class of problems has a wide and important set of applications, from the distribution of goods to the integrated chip design. Rooted on the use of collective intelligence, swarm-inspired algorithms, more specifically bee-inspired approaches, have been used with good performance to solve such problems. In this context, the present paper provides a broad review on the use of bee-inspired methods for solving vehicle routing problems, introduces a new approach to solve one of the main tasks in this area (the travelling salesman problem), and describes open problems in the field.

scholarly journals Penentuan Rute Pengiriman Ice Tube di Kota Malang dengan Algoritma Genetika

2020 ◽  
Vol 11 (1) ◽  
pp. 10
Author(s):  
Nurina Savanti Widya Gotami ◽  
Yane Marita Febrianti ◽  
Robih Dini ◽  
Hamim Fathul Aziz ◽  
San Sayidul Akdam Augusta ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Travelling Salesman Problem ◽  
Combinatorial Problem ◽  
Np Hard ◽  
Travelling Salesman ◽  
Shortest Route ◽  
Reproduction Process ◽  
Delivery Routes ◽  
Np Hard Problem ◽  
Selection Parameter

Abstract. Determining routes for ice tube delivery in Malang is a complex combinatorial problem classified as NP-hard problem. This study aims for optimizing the sales travel routes determination for the delivery to several customers by considering the efficiency of distance traveled. This problem is modeled in the form of Multi Salesman Traveling Problem. Genetic algorithm was used to optimize the determination of ice tube delivery routes that must be taken by each sales. Problems were coded by using permutation representation in which order crossover and swap mutation methods were used for the reproduction process. The process of finding solution was done by using elitism selection. The best genetic algorithm parameters obtained from the test results are the number of iterations of 40 and the population of 40, with the shortest route of 30.3 km. The final solution given by the genetic algorithm is in the form of a travel route that must be taken by each ice tube sales.Keywords: genetic algorithm, mutli travelling salesman problem, optimization, routeAbstrak. Penentuan rute pengiriman ice tube di kota Malang merupakan permasalahan kombinatorial kompleks yang diklasifikasikan sebagai permasalahan NP-hard. Penelitian ini bertujuan untuk melakukan optimasi dalam pembentukan rute perjalanan sales dalam melakukan pengiriman ke beberapa pelanggan dengan mempertimbangkan efisiensi jarak tempuh. Permasalahan ini dimodelkan dalam bentuk Multi Salesman Travelling Problem. Algoritme genetika digunakan untuk mengoptimalkan pembentukan rute pengiriman ice tube yang harus dilalui oleh setiap sales. Permasalahan dikodekan menggunakan representasi permutasi, dengan proses reproduksi menggunakan metode order crossover dan swap mutation. Proses pencarian solusi dilakukan menggunakan elitism selection. Parameter algoritme genetika terbaik yang didapatkan dari hasil pengujian adalah banyaknya iterasi sebesar 40 dan banyaknya populasi sebesar 40, dengan rute terpendek sebesar 30.3 km. Solusi akhir yang diberikan oleh algoritme genetika berupa rute perjalanan yang harus ditempuh oleh setiap sales ice tube.Kata Kunci: algoritme genetika, multi travelling salesman problem, optimasi, rute

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 Travelling Santa Problem: Optimization of a Million-Households Tour Within One Hour

2021 ◽  
Vol 8 ◽  
Author(s):  
Tilo Strutz
Keyword(s):  
Computational Complexity ◽  
Optimization Problems ◽  
State Of The Art ◽  
Travelling Salesman Problem ◽  
Limited Time ◽  
Two Dimensional ◽  
Optimal Solutions ◽  
Major Difficulty ◽  
Travelling Salesman ◽  
New Approach

Finding the shortest tour visiting all given points at least ones belongs to the most famous optimization problems until today [travelling salesman problem (TSP)]. Optimal solutions exist for many problems up to several ten thousand points. The major difficulty in solving larger problems is the required computational complexity. This shifts the research from finding the optimum with no time limitation to approaches that find good but sub-optimal solutions in pre-defined limited time. This paper proposes a new approach for two-dimensional symmetric problems with more than a million coordinates that is able to create good initial tours within few minutes. It is based on a hierarchical clustering strategy and supports parallel processing. In addition, a method is proposed that can correct unfavorable paths with moderate computational complexity. The new approach is superior to state-of-the-art methods when applied to TSP instances with non-uniformly distributed coordinates.

The Travelling Salesman Problem for finite-sized cities

2010 ◽  
Vol 20 (6) ◽  
pp. 1067-1078 ◽  
Author(s):  
HUGO FORT ◽  
MORDECHAI KORNBLUTH ◽  
FREDY ZYPMAN
Keyword(s):  
Travelling Salesman Problem ◽  
Spatial Extent ◽  
Travelling Salesman ◽  
New Approach ◽  
Standard Problem ◽  
First Approximation ◽  
Particular Solution ◽  
New Algorithms

We consider a variation of the Travelling Salesman Problem (TSP) in which the cities visited have non-zero spatial extent, in contrast with the classical TSP, which has destinations that are mathematical points. This new approach opens up both new analyses of the problem and new algorithms for solutions, while remaining an economic first approximation to the standard problem. We present one particular solution that, depending on the number and size of the cities, can improve existing algorithms solving the classical TSP.

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.

Sign in / Sign up

Export Citation Format

Share Document