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Applications of the ant algorithm to combinatorial optimization

TLDR
This paper further extends the idea of this new biological optimization strategy to some other hard combinatorial optimization problems, including the multi attribute situation which lack of efficient solving methods.
Abstract
Ant algorithm is a newly emerged stochastic searching optimization algorithm in recent years It has been paid much attention to since the successful application in the famous travelling salesman problem This paper further extends the idea of this new biological optimization strategy to some other hard combinatorial optimization problems, including the multi attribute situation which lack of efficient solving methods The ability of optimization for the algorithm is tested experimentally which give encouraging results

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Journal ArticleDOI

An improved ant colony optimisation algorithm for three-tier supply chain scheduling based on networked manufacturing

TL;DR: In this paper, a three-tier supply chain scheduling model composed of manufacturer, collaborative design enterprise and customer is proposed to derive a scheduling strategy among supply chain members based on networked manufacturing.
Proceedings ArticleDOI

BEST-WORST Ant System

TL;DR: Experimental results on TSP show that The BWAS algorithm has a better global searching ability, higher convergence speed and solution diversity than that of classical ACO algorithm.
Proceedings ArticleDOI

Research on Ant Colony algorithm for the QAP-based facility layout problems

TL;DR: This paper design the modified ant algorithm for solving the facility layout problem (FLP) based on Ant Colony algorithm by increasing the operator of making solution feasible and shows that the algorithm has strong capability of global search and rapid speed of convergence.
Proceedings ArticleDOI

An Improved Ant System Algorithm Based on PPL

TL;DR: The new algorithm presented has a better global searching ability, higher convergence speed and solution diversity than that of classical ACO algorithm, and makes full use of multi-core CPU's computing power and improves the efficiency significantly.
Journal ArticleDOI

Studies on Properties of Ants System

TL;DR: Several parameters concerned, include: ant initial number m, transfer control parameter q0, importance of visibility β and stigmergy decay parameter, are analyzed, which is of reference significance.
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