An Algorithm to Supply Chain Configuration Based on Ant System

2016 ◽  
pp. 24-35
Author(s):  
Luis A. Moncayo-Martínez
Keyword(s):  
Ant Colony Algorithm ◽  
Minimum Cost ◽  
Ant Colony ◽  
Ant Colony Optimisation ◽  
Ant System ◽  
New Approach ◽  
Pareto Sets ◽  
Multi Agent ◽  
Supply Chain Configuration ◽  
The Cost

This work proposes a new approach, based on Ant Colony Optimisation (ACO), to configure Supply Chains (SC) so as to deliver orders on due date and at the minimum cost. For a set of orders, this approach determines which supplier to acquire components from and which manufacturer will produce the products as well as which transportation mode must be used to deliver products to customers. The aforementioned decisions are addressed by three modules. The data module stores all data relating to SC and models the SC. The optimization engine is a multi-agent framework called SC Configuration by ACO. This module implements the ant colony algorithm and generates alternative SC configurations. Ant-k agent configures a single SC travelling by the network created by the first agent. While Ant-k agent visits a stage, it selects an option to perform a stage based on the amount of pheromones and the cost and lead time of the option. We solve a note-book SC presented in literature. Our approach computes pareto sets with SC design which delivers product from 38 to 91 days.

scholarly journals Clustering Control of Multi-Objective Problems with Application to E-commerce

2018 ◽  
Vol 1 (1) ◽  
pp. 41
Author(s):  
Liang Chen ◽  
Xingwei Wang ◽  
Jinwen Shi
Keyword(s):  
Ant Colony Algorithm ◽  
Time Window ◽  
Ant Colony ◽  
Distribution Area ◽  
Routing Problem ◽  
Logistics Distribution ◽  
Multi Objective ◽  
The Cost ◽  
Vehicle Capacity ◽  
Cost Of Transportation

In the existing logistics distribution methods, the demand of customers is not considered. The goal of these methods is to maximize the vehicle capacity, which leads to the total distance of vehicles to be too long, the need for large numbers of vehicles and high transportation costs. To address these problems, a method of multi-objective clustering of logistics distribution route based on hybrid ant colony algorithm is proposed in this paper. Before choosing the distribution route, the customers are assigned to the unknown types according to a lot of customers attributes so as to reduce the scale of the solution. The discrete point location model is applied to logistics distribution area to reduce the cost of transportation. A mathematical model of multi-objective logistics distribution routing problem is built with consideration of constraints of the capacity, transportation distance, and time window, and a hybrid ant colony algorithm is used to solve the problem. Experimental results show that, the optimized route is more desirable, which can save the cost of transportation, reduce the time loss in the process of circulation, and effectively improve the quality of logistics distribution service.

The Research on VRP Based on Max-Min Ant Colony Algorithm

2011 ◽  
Vol 219-220 ◽  
pp. 1285-1288 ◽  
Author(s):  
Chang Min Chen ◽  
Wei Cheng Xie ◽  
Song Song Fan
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Ant Colony Algorithm ◽  
Search Time ◽  
Ant Colony ◽  
Local Optimum ◽  
Simulation Data ◽  
Routing Problem ◽  
Np Hard Problem ◽  
The Cost

Vehicle routing problem (VRP) is the key to reducing the cost of logistics, and also an NP-hard problem. Ant colony algorithm is a very effective method to solve the VRP, but it is easy to fall into local optimum and has a long search time. In order to overcome its shortcomings, max-min ant colony algorithm is adopted in this paper, and its simulation system is designed in GUI of MATLAB7.0. The results show that the vehicle routing problem can well achieves the optimization of VRP by accessing the simulation data of database.

A Meta-Heuristic with Ant Colony Approach to Complex System

2010 ◽  
Vol 26-28 ◽  
pp. 1147-1150
Author(s):  
Zong Li Liu ◽  
Jie Cao ◽  
Zhan Ting Yuan
Keyword(s):  
Complex System ◽  
System Design ◽  
Ant Colony ◽  
Pareto Optimal ◽  
Ant Colony Optimisation ◽  
New Approach ◽  
Pareto Optimal Set ◽  
Simulation Results ◽  
Optimal Set ◽  
Complex System Design

This paper proposes a new approach to determining the complex system design for a product mix comprising complex hierarchies of subassembly and components. Pareto Ant Colony Optimisation as an especially effective meta-heuristic for solving the problem of complex system design was introduced in this paper. A Pareto Optimal Set of complex system in which only the non dominated solutions allow ants to deposit pheromones over the time and cost pheromone matrices after certain generation runs. Simulation results show that the model for complex system and the hybrid algorithms are effective to the design of complex system.

scholarly journals OPTIMASI RUTE PANDUAN INFORMASI LOKASI WISATA MENGGUNAKAN ANT COLONY SYSTEM PADA KOTA BATAM

2019 ◽  
Vol 2 (2) ◽  
pp. 1-13
Author(s):  
Alfannisa Annurrallah Fajrin ◽  
Delia Meldra
Keyword(s):  
Ant Colony Algorithm ◽  
Path Selection ◽  
Ant Colony ◽  
Ant Colony System ◽  
Tourist Attractions ◽  
Tourist Destinations ◽  
The People ◽  
Waterfall Model ◽  
The Cost ◽  
The City

The number of tourists visiting the city of Batam both domestic and foreign tourists to spend their vacation time because the cost of living and goods are cheaper than other areas because batam is an FTZ area (free tax Zone). So that the city of Batam has become a shopping paradise for the people around Batam or outside Batam. Batam itself has several shopping destinations and places to visit for tourists. With the abundance of tourist destinations in the city of Batam, both shopping and nature tourism, it is not uncommon for tourists to experience various problems in visiting the country, one of the simple problems experienced is the problem of time and cost efficiency in conducting tours to the city of Batam. The problem that we can solve in this research is to help tourists or tourists not experience difficulties when visiting tourist attractions in Batam by using the ant colony algorithm in efficient path selection. The Waterfall Model in SDLC is a process that will be used in this study to get the best results.

scholarly journals Research on Optimal Matching Scheme of Public Resource Management Based on the Computational Intelligence Model

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Linna Li ◽  
Renjun Liu
Keyword(s):  
Genetic Algorithm ◽  
Human Resources ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Time Consumption ◽  
Public Resource ◽  
Public Resources ◽  
Benefit Function ◽  
The Cost ◽  
Better Than

The management of public resources means that people’s governments at all levels and other public administrative subjects should use certain means and methods, follow certain principles, rationally allocate and utilize public resources, and maximize their functions and benefits. Under the background of limited human resources, this study adheres to the principle of maximizing the benefits of human resources and rationally allocates the use of human resources. In this study, this kind of resource allocation problem is regarded as a linear programming problem by specifying the benefit function, and then, genetic algorithm, ant colony algorithm, and hybrid genetic-ant colony algorithm are used to solve the problem; the cost and time consumption of different algorithms under different scales are evaluated. Finally, it is found that genetic algorithm is superior to ant colony algorithm when the task scale is small and the effect of genetic algorithm is lower than ant colony algorithm with the expansion of task scale, whereas the improved hybrid genetic-ant colony algorithm is better than ordinary algorithm in general.

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