The protein side chain packing problem (PSCPP) is an essential issue for predicting structure in proteomics. PSCPP has been proved to be NP-hard. In this paper, we propose a method for solving PSCPP by transforming it to the graph clique problem, and then applying the ant colony optimization (ACO) algorithm to solve it. We build the coordinate rotamer library based on the pair of dihedral angle...

Within the Artificial Intelligence community, there is great need for fast and accurate traversal algorithms, specifically those that find a path from a start to goal with minimum cost. Cost can be distance, time, money, energy, etc. Travelling salesman problem (TSP) is a combinatorial optimization problem. TSP is the most intensively studied problem in the area of optimization. Ant colony opti...

Ant colony optimization (ACO) is a metaheuristic that produces good results for a wide range of combinatorial optimization problems. Often such successful applications use a combination of ACO and local search procedures that improve the solutions constructed by the ants. In this paper, we study this combination from a theoretical point of view and point out situations where introducing local s...

Biogeography based optimization (BBO) and ant colony optimization (ACO) to develop global optimization path. In natural scenario, there are no prior paths and we don't have any prior information about any geographical area. The key factor to achieve a task in such area is Path planning; therefore this research direction is very useful in recent years. This hybrid approach describes autonomous n...

Accurate forecasting of electric load has always been the most important issues in the electricity industry, particularly for developing countries. Due to the various influences, electric load forecasting reveals highly nonlinear characteristics. This paper creates a system for power load forecasting using support vector machine and ant colony optimization. The method of colony optimization is ...

Groundwater long-term monitoring (LTM) is required to assess human health and environmental risk of residual contaminants after active groundwater remediation activities are completed. However, LTM can be costly because of the large number of sampling locations that exist at a site from previous site characterization and remediation activities. The cost of LTM may be reduced by identifying redu...

Biological inspired routing or bio-inspired routing is a new heuristic routing algorithm in wireless sensor network, which is inspired from biological activities of insects. ACO is ants’ inspired routing algorithm ACO, which has the ability to find shortest path and re-establish the new route in the case of route failure. In order to improve the network performance i.e. increase network lifetim...

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...

The paper presents a methodology to arrive at optimal truss designs using Ant Colony Optimization (ACO) algorithms. Ant Colony Optimization is a population-based, artificial multi-agent, general-search technique for the solution of difficult combinatorial problems with its theoretical roots based on the behavior of real ant colonies and the collective trail-laying and trail-following of its mem...

In this paper, a new approach for designing an adaptive fuzzy model predictive control (AFMPC) based on the ant colony optimization (ACO) is proposed. On-line adaptive fuzzy identification is introduced to identify the system parameters. These parameters are used to calculate the objective function based on a predictive approach and structure of RST control. Then the optimization problem is sol...