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...

clustering technique is one of the most important techniques of data mining and is the branch of multivariate statistical analysis and a method for grouping similar data in to same clusters. with the databases getting bigger, the researchers try to find efficient and effective clustering methods so that they can make fast and real decisions. thus, in this paper, we proposed an improved ant syst...

Wireless Sensor Networks (WSNs) have been attracting the attention of both academic and industrial research communities for the past few years. To find an optimal topology control strategy in 3-dimensional (3D) WSNs is a new challenge. In this paper, we discuss issues related to the topology control in 3D WSNs, review a 2D model for WSNs, and introduce a 3D model for WSNs. An Immunity-Based Ant...

Swarm robotic is a new research area in the domain of Artificial intelligence. Particularly, the swarm robot concept is adopted from Mother Nature that combines small robots in a group to solve a particular problem. This work presents decentralization of swarm robots along-with their methods of optimization, development, applications and implementation in real life domain. It also solves the tr...

Limited amount of time and computational resources in industrial domain makes Ant Colony Optimization (ACO) a useful approach to find near optimal solutions in polynomial time for Nondeterministic Polynomial time (NP) problems. For dynamically changing graphs, such as in case of network routing and urban transportation systems which are based on Travelling Salesman Problem (TSP), the ant colony...

Ant Colony optimization has proved suitable to solve a wide range of combinatorial optimization (or NP-hard) problems as the Travelling Salesman Problem (TSP). The first step of ACO algorithm is to set the parameters that drive the algorithm. The parameter has an important impact on the performance of the ant colony algorithm. The basic parameters that are used in ACO algorithms are; the relati...

The study of the buyer coalition has been reviewed by researchers for decades. However, there are few schemes applying ant colony optimization (ACO) for forming buyer coalition. In this paper, the approach called the Ant Colony for Buyer Coalition (ACBC) algorithm is proposed to form the buyer coalition with bundles of items. The main endeavor of the algorithm is to partition the whole group of...