The Nested Partition algorithm suffers from the lack of information gathering and sharing despite the computational effort dedicated to sampling the different subregions at each step of the algorithm. It is also noticed that the solution quality of the NP algorithm largely depends on the quality of the samples generated. Ants are used in this work as a mean to improve the samples quality throug...

In this paper, we propose a new ant-based clustering algorithm called AntClust. It is inspired from the chemical recognition system of ants. In this system, the continuous interactions between the nestmates generate a “Gestalt” colonial odor. Similarly, our clustering algorithm associates an object of the data set to the odor of an ant and then simulates meetings between ants. At the end, artif...

-NP-hard problem can be solved by Ant Colony System (ACS) algorithm. However, ACS suffers from pheromone stagnation problem, a situation when all ants converge quickly to one sub-optimal solution. ACS algorithm utilizes the value between nodes as heuristic value to calculate the probability of choosing the next node. However, the heuristic value is not updated throughout the process to reflect ...

Background: Synanthropic ants can transmit pathogens especially in hospital environments,  but this fact had not been confirmed in Palaearctic region. This is the first study on confirming this ability of ants in this region. Methods: Three hospitals of Bandar Abbas, Iran have been selected for monthly sampling of ants in their various wards. The main processe...

The scheduling problem for ̄exible manufacturing systems (FMSs) has been attempted in this paper using the ant colony optimization (ACO) technique. Since the operation of a job in FMSs can be performed on more than one machine, the scheduling of the FMS is considered as a computationally hard problem. Ant algorithms are based on the foraging behaviour of real ants. The article deals with the an...

Enlightened by the behaviors of gregarious ant colonies, an artificial ant movement (AM) model and an adaptive ant clustering (AAC) algorithm for this model are presented. In the algorithm, each ant is treated as an agent to represent a data object. In the AM model, each ant has two states: sleeping state and active state. In the algorithm AAC, the ant’s state is controlled by both a function o...

Abs t rac t . In this paper we introduce an Ant Colony Optimisation (ACO) algorithm for the Shortest Common Supersequence (SCS) problem, which has applications in production system planning, mechanical engineering and molecular biology. The ACO algorithm is used to find good parameters for a heuristic for the SCS problem. An island model with several populations of ants is used for the ACO algo...

In this extended abstract we present an algorithm based on the Ant Colony Optimization (ACO) metaheuristic for the single machine total weighted tardiness problem, a well known NP–hard scheduling problem. Our ACO algorithm is currently among the best algorithms known for this problem type. In particular, we will discuss three elements that enable it to find very good solutions quickly. These ar...

Ant colony optimisation algorithms (ACO) work via a process called stigmergy in which ants deposit pheromone traces in order to influence foraging patterns. Pheromone traces are picked up and followed by other ants but they evaporate over time. Paths with more pheromone will survive longer and have a higher chance of getting followed and reinforced whilst weaker traces simply fade away. The pre...

A new kind of Ant Colony Optimization (ACO) algorithm is proposed that is suitable for an implementation in hardware. The new algorithm — called Counter-based ACO — allows to systolically pipe artificial ants through a grid of processing cells. Various features of this algorithm have been designed so that it can be mapped easily to Field-Programmable Gate Arrays (FPGAs). Examples are a new enco...