An adaptive parallel ant colony optimization is presented by improving the critical factor influencing the performance of the parallel algorithm. We propose two different strategies for information exchange between processors: selection based on sorting and on difference, which make each processor choose another processor to communicate and update the pheromone adaptively. In order to increase ...

................................................................................................................................. I ACKNOWLEDGEMENTS ..................................................................................................... III TABLE OF CONTENTS ......................................................................................................... IV

The ant colony optimisation metaheuristic has shown promise on simplified artificial instances of university course timetabling problems. However, limited work has been done applying it to practical timetabling problems. In this paper, we describe the application of the ant colony optimisation to a highly constrained real–world instance of the university course timetabling problem. We present t...

This paper mainly addresses the balance control of a ball and beam system, where a pair of decoupled fuzzy sliding-mode controllers (DFSMCs) are proposed. The DFSMC has the advantage of reducing the design complexity, in which the coupling dynamics of the state-error dynamics are considered as disturbance terms. Stability analysis of the ball and beam system with DFSMCs is also discussed in det...

In this paper, we propose a variant of an ACO algorithm called the cunning Ant System (cAS). In cAS, each ant generates a solution by borrowing a part of a solution which was generated in previous iterations, instead of generating the solution entirely from pheromone density. Thus we named it, cunning ant. This cunning action reduces premature stagnation and exhibits good performance in the sea...

In this paper we present an approximation algorithm for the p-median problem that uses the principles of ant colony optimization technique. We introduce a search tree that keeps the partial solutions during the solution process of the p-median problem. An adaptation is proposed that allows ant colony optimization algorithm to perform on this tree and obtain good results in short time.

In view of shortcomings of BP neural network, which is slow to converge and tends to trap in local optimum when applied in fault diagnosis, an approach for fault diagnosis based on BP neural network optimized by chaos ant colony algorithm is proposed. Mathematical model of chaos ant colony algorithm is created. Real-coded method is adopted and the weights and thresholds of BP neural network are...

A novel version of Ant Colony Optimization (ACO) algorithms for solving continuous space problems is presented in this paper. The basic structure and concepts of the originally reported ACO are preserved and adaptation of the algorithm to the case of continuous space is implemented within the general framework. The stigmergic communication is simulated through considering certain direction vect...

this paper considers the job scheduling problem in virtual manufacturing cells (vmcs) with the goal of minimizing two objectives namely, makespan and total travelling distance. to solve this problem two algorithms are proposed: traditional non-dominated sorting genetic algorithm (nsga-ii) and knowledge-based non-dominated sorting genetic algorithm (kbnsga-ii). the difference between these algor...