scholarly journals IMPLEMENTASI ALGORITMA I-SOS DALAM PENYELESAIAN TRAVELING SALESMAN PROBLEM (TSP)

2021 ◽  
Vol 2 (1) ◽  
pp. 1-7
Author(s):  
Zulkarnaen Zulkarnaen ◽  
Muhammad Azmi
Keyword(s):  
Traveling Salesman Problem ◽  
Minimum Distance ◽  
Random Number ◽  
Traveling Salesman ◽  
Shortest Distance ◽  
The City ◽  
Destination City

The problem with TSP is an attempt to find the shortest distance traveled by a salesman in visiting each city without having to visit the same city more than once. The purpose of implementing the I-SOS algorithm in this case is to find the minimum distance traveled, a solution can be obtained after going through the calculation of the mutualism phase, commensalism phase, parasitism phase and predation phase. The resolution of TSP problems in the study begins with the process of identifying each city by providing a random value to represent each destination city. The random value used is between 0 and 1, the random results obtained will then be sorted with the provision that the smallest random value will be used as the initial for city A while the largest random value is used as the initial for city D. In the first random, the random value | 0.5 | 0.27 | 0.75 | 0.25 | the city representation of the random number is | C | B | D | A | or if the values are sorted, the city order will be obtained, namely A = 0.25, B = 0.27, C = 0.5 and D = 0.75, this process will continue until all the organisms defined in the ecosystem are formed

ASIF Approach to Solve the Green Traveling Salesman Problem

2018 ◽  
Vol 9 (1) ◽  
pp. 81-95 ◽  
Author(s):  
Ahmed Haroun Sabry ◽  
Jamal Benhra ◽  
Abdelkabir Bacha
Keyword(s):  
Objective Function ◽  
Ant Colony Optimization ◽  
Present Article ◽  
Traveling Salesman Problem ◽  
Real World ◽  
Transportation Problem ◽  
Problem Formulation ◽  
Traveling Salesman ◽  
Web Based ◽  
The City

The present article describes a contribution to solve transportation problems with green constraints. The aim is to solve an urban traveling salesman problem where the objective function is the total emitted CO2. We start by adapting ASIF approach for calculating CO2 emissions to the urban logistics problem. Then, we solve it using ant colony optimization metaheuristic. The problem formulation and solving will both work under a web-based mapping platform. The selected problem is a real-world NP-hard transportation problem in the city of Casablanca.

scholarly journals PENYELESAIAN MULTI TRAVELING SALESMAN PROBLEM DENGAN ALGORITMA GENETIKA

2017 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
NI KADEK MAYULIANA ◽  
EKA N. KENCANA ◽  
LUH PUTU IDA HARINI
Keyword(s):  
Genetic Algorithm ◽  
Traveling Salesman Problem ◽  
Heuristic Algorithm ◽  
Minimum Distance ◽  
Processing Time ◽  
Traveling Salesman ◽  
Running Time ◽  
Shortest Route ◽  
Time Required

Genetic algorithm is a part of heuristic algorithm which can be applied to solve various computational problems. This work is directed to study the performance of the genetic algorithm (GA) to solve Multi Traveling Salesmen Problem (multi-TSP). GA is simulated to determine the shortest route for 5 to 10 salesmen who travelled 10 to 30 cities. The performance of this algorithm is studied based on the minimum distance and the processing time required for 10 repetitions for each of cities-salesmen combination. The result showed that the minimum distance and the processing time of the GA increase consistently whenever the number of cities to visit increase. In addition, different number of sales who visited certain number of cities proved significantly affect the running time of GA, but did not prove significantly affect the minimum distance.

scholarly journals Travelling Salesman Problem Analysis with Complete Enumeration Method, Branch & Bound and Greedy Heuristic

2021 ◽  
Vol 1 (8) ◽  
pp. 752-756
Author(s):  
Ifham Azizi Surya Syafiin ◽  
Sarah Nur Fatimah ◽  
Muchammad Fauzi
Keyword(s):  
Traveling Salesman Problem ◽  
Travelling Salesman Problem ◽  
Traveling Salesman ◽  
Greedy Heuristic ◽  
Problem Analysis ◽  
Heuristic Methods ◽  
Travelling Salesman ◽  
Complete Enumeration ◽  
The Traveling Salesman Problem ◽  
The City

PT XYZ as the best and largest Bed Sheet Set company in Indonesia with products such as Bed Covers, Bed Sheets, Pillowcases, Bolsters and Blankets. The Traveling Salesman Problem (TSP) is a problem faced in finding the best route to visit shops that sell products from PT BIG. A visit to the shop is carried out on the condition that each city can only be visited once except the city of origin. The algorithms applied in this TSP problem include the Complete Enumeration, Branch & Bound and Greedy Heuristic methods.

scholarly journals Developing an Android-Based City Tour App using Evolutionary Algorithm

2021 ◽  
Vol 15 (14) ◽  
pp. 193
Author(s):  
Abidatul Izzah ◽  
Irmala Arin Kusuma ◽  
Yudi Irawan ◽  
Toga Aldila Cinderatama ◽  
Benni Agung Nugroho
Keyword(s):  
Genetic Algorithm ◽  
Evolutionary Algorithm ◽  
Mobile Devices ◽  
Traveling Salesman Problem ◽  
Traveling Salesman ◽  
Brute Force ◽  
Running Time ◽  
Force Method ◽  
Brute Force Method ◽  
The City

Traveling around a city and making transit in certain areas is called a city tour. Furthermore, determining the optimal city tour route can be considered as a traveling salesman problem. There are many kinds of algorithms to solve this, one of which is the Genetic Algorithm (GA). In developing the City Tour application, a platform is needed to be taken to various places anywhere and anytime. Finally, we developed an application that runs on mobile devices. This application is built on the Android platform so that its use can be more efficient. Furthermore, it can be concluded that the GA applied to the Android-based City Tour Application is reliable to determine city tour routes; this is evidenced by comparing GA with the brute force method, where GA provides optimum results with less running time.

scholarly journals Indoor Traveling Salesman Problem (ITSP) Path Planning

2021 ◽  
Vol 10 (9) ◽  
pp. 616
Author(s):  
Jinjin Yan ◽  
Sisi Zlatanova ◽  
Jinwoo (Brian) Lee ◽  
Qingxiang Liu
Keyword(s):  
Path Planning ◽  
Traveling Salesman Problem ◽  
Indoor Navigation ◽  
Traveling Salesman ◽  
Shopping Mall ◽  
Navigation Systems ◽  
Quick Response ◽  
Navigation Path ◽  
Shortest Distance ◽  
Increasing Demand

With the growing complexity of indoor living environments, people have an increasing demand for indoor navigation. Currently, navigation path options in indoor are monotonous as existing navigation systems commonly offer single-source shortest-distance or fastest paths. Such path options might be not always attractive. For instance, pedestrians in a shopping mall may be interested in a path that navigates through multiple places starting from and ending at the same location. Here, we name it as the indoor traveling salesman problem (ITSP) path. As its name implies, this path type is similar to the classical outdoor traveling salesman problem (TSP), namely, the shortest path that visits a number of places exactly once and returns to the original departure place. This paper presents a general solution to the ITSP path based on Dijkstra and branch and bound (B&B) algorithm. We demonstrate and validate the method by applying it to path planning in a large shopping mall with six floors, in which the QR (Quick Response) codes are assumed to be utilized as the indoor positioning approach. The results show that the presented solution can successfully compute the ITSP paths and their potentials to apply to other indoor navigation applications at museums or hospitals.

A Clarke and Wright Improved Algorithm to Solve the Vehicle Routing and Traveling Salesman Problem

2016 ◽  
Vol 8 (1) ◽  
pp. 35
Author(s):  
Mamoon Alameen ◽  
Rasha Aljamal ◽  
Sadeq Damrah
Keyword(s):  
Vehicle Routing ◽  
Traveling Salesman Problem ◽  
Vehicle Routing Problem ◽  
Traveling Salesman ◽  
Exact Methods ◽  
Routing Problem ◽  
Cpu Time ◽  
Shortest Distance ◽  
Transportation Scheduling ◽  
The Given

Vehicle Routing Problem (VRP) and Traveling Salesman Problem (TSP) are well known transportation problems. The problems can be seen in all the industries that involves goods distribution and transportation scheduling. Finding the shortest distance with respect to the given constraint contribute highly to save money and energy consumption. This paper investigates the possibility of creating a cellular application that can provide an instant routing plan through a simple heuristic (Clarke and Wright) in order to avoid the usage of more complicated approaches as metaheuristics and exact methods that normally taking very long CPU time.

scholarly journals PARALLEL TEMPERING FOR THE TRAVELING SALESMAN PROBLEM

2009 ◽  
Vol 20 (04) ◽  
pp. 539-556 ◽  
Author(s):  
CHIAMING WANG ◽  
JEFFREY D. HYMAN ◽  
ALLON PERCUS ◽  
RUSSEL CAFLISCH
Keyword(s):  
Simulated Annealing ◽  
Combinatorial Optimization ◽  
Traveling Salesman Problem ◽  
Minimum Distance ◽  
Optimization Problems ◽  
Optimization Method ◽  
Traveling Salesman ◽  
Parallel Tempering ◽  
Combinatorial Optimization Problems ◽  
The Traveling Salesman Problem

We explore the potential of parallel tempering as a combinatorial optimization method, applying it to the traveling salesman problem. We compare simulation results of parallel tempering with a benchmark implementation of simulated annealing, and study how different choices of parameters affect the relative performance of the two methods. We find that a straightforward implementation of parallel tempering can outperform simulated annealing in several crucial respects. When parameters are chosen appropriately, both methods yield close approximation to the actual minimum distance for an instance with 200 nodes. However, parallel tempering yields more consistently accurate results when a series of independent simulations are performed. Our results suggest that parallel tempering might offer a simple but powerful alternative to simulated annealing for combinatorial optimization problems.

scholarly journals An Application of Genetic Algorithm in Determining Salesmen’s Routes: A Case Study

2018 ◽  
Vol 17 (1) ◽  
pp. 26
Author(s):  
Noufal Zhafira ◽  
Feri Afrinaldi ◽  
Taufik Taufik
Keyword(s):  
Genetic Algorithm ◽  
Traveling Salesman Problem ◽  
Pharmaceutical Products ◽  
Traveling Salesman ◽  
Future Research ◽  
Distribution Problem ◽  
Distribution Company ◽  
Time Required ◽  
The City

This paper presents a case study of determining vehicles’ routes. The case is taken from a pharmaceutical products distribution problem faced by a distribution company located in the city of Padang, Indonesia. The objective of this paper is to reduce the total distribution time required by the salesmen of the company. Since the company uses more than one salesman, then the problem is modeled as a multi traveling salesman problem (m-TSP). The problem is solved by employing genetic algorithm (GA) and a Matlab® based computer program is developed to run the algorithm. It is found that, by employing two salesmen only, the routes produced by GA results in a 30% savings in total distribution time compared to the current routes used by the company (currently the company employs three salesmen). This paper determines distances based on the latitude and longitude of the locations visited by the salesmen. Therefore, the distances calculated in this paper are approximations. It is suggested that actual distances are used for future research.

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