A novel traffic routing method using hybrid Ant Colony System based on genetic algorithm

2017 ◽  
Author(s):  
Dang-Nhac Lu ◽  
Thi-Hau Nguyen ◽  
Thi-Thu-Trang Ngo ◽  
Duc-Nhan Nguyen ◽  
Ha-Nam Nguyen
Keyword(s):  
Genetic Algorithm ◽  
Ant Colony ◽  
Ant Colony System ◽  
Traffic Routing ◽  
Routing Method

Building optimal regression tree by ant colony system–genetic algorithm: Application to modeling of melting points

2011 ◽  
Vol 704 (1-2) ◽  
pp. 57-62 ◽  
Author(s):  
Bahram Hemmateenejad ◽  
Mojtaba Shamsipur ◽  
Vali Zare-Shahabadi ◽  
Morteza Akhond
Keyword(s):  
Genetic Algorithm ◽  
Regression Tree ◽  
Ant Colony ◽  
Ant Colony System ◽  
Melting Points

scholarly journals An Integrated Metaheuristic Routing Method for Multiple-Block Warehouses with Ultranarrow Aisles and Access Restriction

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Fangyu Chen ◽  
Gangyan Xu ◽  
Yongchang Wei
Keyword(s):  
Genetic Algorithm ◽  
Ant Colony Optimization ◽  
Hybrid Algorithm ◽  
Routing Algorithm ◽  
Ant Colony ◽  
Optimal Solutions ◽  
Solution Quality ◽  
Service Efficiency ◽  
Routing Method ◽  
Simulation Results

A problem-specific routing algorithm integrating ant colony optimization (ACO) and integer-coded genetic algorithm (GA) is developed to address the newly observed limitations imposed by ultranarrow aisles and access restriction, which exist in the largest e-commerce enterprise with self-run logistics in China. Those limitations prohibit pickers from walking through the whole aisle, and the access restriction even allows them to access the pick aisles only from specific entrances. The ant colony optimization is mainly responsible for generating the initial chromosomes for the genetic algorithm, which then searches the near-optimal solutions of picker-routing with our novel chromosome design by recording the detailed information of access modes and subaisles. To demonstrate the merits of the proposed algorithm, a comprehensive simulation for comparison is conducted with 12 warehouse layouts with real order information. The simulation results show that the proposed hybrid algorithm is superior to dedicated heuristics in terms of solution quality. The impacts of the parameters with respect to warehouse layout on the picking efficiency are analyzed as well. Setting more connect aisles and cross aisles is suggested to effectively optimize the picking-service efficiency in the presence of access limitations.

scholarly journals IMPLEMENTASI ALGORITMA GENETIKA DALAM PENENTUAN RUTE TERBAIK PENDISTRIBUSIAN BBM PADA PT BURUNG LAUT

2017 ◽  
Vol 3 (1) ◽  
Author(s):  
I Wayan Supriana
Keyword(s):  
Genetic Algorithm ◽  
Travelling Salesman Problem ◽  
Test System ◽  
Ant Colony ◽  
Fuel Oil ◽  
Ant Colony System ◽  
Travelling Salesman ◽  
The People ◽  
System Method ◽  
Genetic Algorithm Method

ABSTRACT<br />Fuel Oil <br />(<br />BBM<br />)<br />is one of the important commodities for the people of Indonesia. BBM is<br />distributed by sea. One of the companies whose fleets are working in the distribution of fuel is PT<br />Burung Laut, which is by operating the Tanker MT. Citra Bintang. This ship distributes fuel to the<br />Maluku and Papua areas. But in its distribution, this ship does not have a definite route. Previous<br />research has been done by Closeary et al. By using Ant Colony System method. In this research,<br />conducted the shortest distance search that is passed by ship with Genetic Algorithm method for<br />case study of Traveling Salesman Problem. From the test system that has been done as much as<br />10 times the shortest route produced with a distance of 4853 kilometers. The route of the ship<br />with the distance is Tobelo, Fak - Fak, Kaimana, Tual, Dobo, Merauke, Saumlaki, Namlea,<br />Ambon, Masohi, Sanana, Labuha, and then Ternate<br />Keywords:<br />Genetic Algorithm, Travelling Salesman Problem<br />ABSTRAK<br />Bahan Bakar Minyak <br />(<br />BBM<br />)<br />adalah salah satu komoditas penting bagi masyarakat Indonesia.<br />BBM didistribusikan melalui jalur laut. Salah satu perusahaan yang armada laut yang bekerja dalam<br />pendistribusian BBM adalah PT Burung Laut, yaitu dengan mengoperasikan Kapal Tanker MT.<br />Citra Bintang. Kapal ini mendistribusikan BBM pada daerah Maluku dan Papua. Namun dalam<br />pendistribusiannya, kapal ini tidak memiliki rute yang pasti. Penelitian sebelumnya sudah pernah<br />dilakukan oleh Tutupary, et al. Dengan menggunakan metode Ant Colony System. Pada penelitian<br />ini, dilakukan pencarian jarak terpendek yang dilewati kapal dengan metode Algoritma Genetika<br />untuk studi kasus Travelling Salesman Problem. Dari pengujian sistem yang telah dilakukan<br />sebanyak 10 kali dihasilkan rute terpendek dengan jarak 4.853 kilometer. Adapun rute yang dilalui<br />kapal dengan jarak tersebut adalah Tobelo, Fak-Fak, Kaimana, Tual, Dobo, Merauke, Saumlaki,<br />Namlea, Ambon, Masohi, Sanana, Labuha, dan kemudian terakhir Ternate.<br />Kata Kunci: Algoritma Genetika, Kasus Pedagang Keliling

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