this paper considers identical parallel machines scheduling problem with past-sequence-dependent setup times, deteriorating jobs and learning effects, in which the actual processing time of a job on each machine is given as a function of the processing times of the jobs already processed and its scheduled position on the corresponding machine. in addition, the setup time of a job on each machin...

-In this paper a hybrid variant of meta-heuristic algorithm ant colony optimization (ACO) is used. Approximate solutions to quadratic assignment problem have been proved very efficient. Different variants of ant colony optimization have been applied to QAP. But in this paper a hybrid approach is proposed which is combination of Ant system and Max-Min Ant system to take benefits of both the meth...

Data Mining is used to discover the knowledge from large amount of databases and transform it into a flexible structure. Association rule mining (ARM) is the essential part of data mining process. Finding good quality of association rules between items in large databases has been an important and challenging association rule mining problem. The rules mined through ARM algorithms are used for de...

We present a dynamic algorithm for solving the Longest Common Subsequence Problem using Ant Colony Optimization Technique. The Ant Colony Optimization Technique has been applied to solve many problems in Optimization Theory, Machine Learning and Telecommunication Networks etc. In particular, application of this theory in NP-Hard Problems has a remarkable significance. Given two strings n a a A ...

A new concept algorithm based on the Ant Colony Optimization is developed for the use in 2-D and 3-D particle tracking velocimetry (PTV). In the particle matching process of PTV, the Ant Colony Optimization is usually aimed at minimization of the sum of the distances between the first-frame and second-frame particles. But this type of minimization often goes unsuccessfully in the regions where ...

The Ant Colony Optimization (ACO) is a metaheuristic inspired by the behavior of real ants in their search for the shortest paths to food sources. It has recently attracted a lot of attention and has been successfully applied to a number of different optimization problems. Due to the importance of the feature selection problem and the potential of ACO, this paper presents a novel method that ut...

In this paper, an algorithm based on ant colony optimization for community detection from bipartite networks is presented. The algorithm establishes a model graph for the ants’ searching. Each ant chooses its path according to the pheromone and heuristic information on each edge to construct a solution. Experimental results show that our algorithm can not only accurately identify the number of ...

The purpose of this article is to review the literature on the topic of deterministic vehicle routing problem (VRP) and to give a review on the exact and approximate solution techniques. More specifically the approximate (meta-heuristic) solution techniques are classified into: tabu search, simulated annealing, genetic algorithm, evolutionary algorithm, hybrid algorithm, and Ant Colony Opti...