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.

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 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 Anchoring the social economy at the metropolitan scale: Findings from the Liverpool City Region

Urban Studies ◽  
2020 ◽  
pp. 004209802097265
Author(s):  
Matthew Thompson ◽  
Alan Southern ◽  
Helen Heap
Keyword(s):  
Economic Development ◽  
Social Economy ◽  
Future Research ◽  
City Region ◽  
Anchor Institutions ◽  
Urban Economic Development ◽  
The Social ◽  
Social Economies ◽  
The City

This article revisits debates on the contribution of the social economy to urban economic development, specifically focusing on the scale of the city region. It presents a novel tripartite definition – empirical, essentialist, holistic – as a useful frame for future research into urban social economies. Findings from an in-depth case study of the scale, scope and value of the Liverpool City Region’s social economy are presented through this framing. This research suggests that the social economy has the potential to build a workable alternative to neoliberal economic development if given sufficient tailored institutional support and if seen as a holistic integrated city-regional system, with anchor institutions and community anchor organisations playing key roles.

Preventing post-disaster population losses and recovery policy

2021 ◽  
Vol 19 (3) ◽  
pp. 240-244
Author(s):  
Joseph L. Richmond, LPD, MPA
Keyword(s):  
Future Research ◽  
Government Officials ◽  
Specific Policy ◽  
Business Officials ◽  
Recovery Processes ◽  
Response And Recovery ◽  
Policy Measures ◽  
Design Case Study ◽  
The City

Objective: On May 22, 2011, an EF-5 tornado struck Joplin, Missouri, leaving behind 161 fatalities and $2.8 billion in economic impacts. This case study of the 2011 disaster was an attempt at determining if and how economic recovery occurred following the disaster through the lived experiences of government officials, local policymakers, and business officials. Design: Case study using in-depth, semistructured, one-on-one interviews and a qualitative design and analysis.Setting: Joplin, Missouri/2011 Joplin Tornado Participants: Seven local government officials, policymakers, and business officials from the city of Joplin that were directly involved in the response and recovery from the 2011 tornado.Interventions: N/AMain outcome measure(s): N/AResults: Policies and actions that were the most effective focused on housing, personal financial resources of the survivors, and ensuring that the recovery processes were expedited as much as prudently possible.Conclusions: Specific policy measures are not recommended through the un-generalizable findings of this case study; however, this case study places a foundation for future research to develop specific policy measures related to disaster recovery.

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.

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