Search results for "Optimization algorithm"
showing 10 items of 51 documents
An ant colony optimization-based fuzzy predictive control approach for nonlinear processes
2015
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 solved based on an ACO algorithm, used at the optimization process in AFMPC to determine optimal controller parameters of RST control. The utility of the proposed controller is demonstrated by applying it to two nonlinear processes, where the proposed approach provides better performances compared with p…
Towards Multilevel Ant Colony Optimisation for the Euclidean Symmetric Traveling Salesman Problem
2015
Ant Colony Optimization ACO metaheuristic is one of the best known examples of swarm intelligence systems in which researchers study the foraging behavior of bees, ants and other social insects in order to solve combinatorial optimization problems. In this paper, a multilevel Ant Colony Optimization MLV-ACO for solving the traveling salesman problem is proposed, by using a multilevel process operating in a coarse-to-fine strategy. This strategy involves recursive coarsening to create a hierarchy of increasingly smaller and coarser versions of the original problem. The heart of the approach is grouping the variables that are part of the problem into clusters, which is repeated until the size…
α-stable distributions for better performance of ACO in detecting damage on not well spaced frequency systems
2014
Abstract In this paper, the Ant Colony Optimization (ACO) algorithm is modified through α -stable Levy variables and applied to the identification of incipient damage in structural components. The main feature of the proposed optimization is an improved ability, which derives from the heavy tails of the stable random variable, to escape from local minima. This aspect is relevant since the objective function used for damage detection may have many local minima which render very challenging the search of the global minimum corresponding to the damage parameter. As the optimization is performed on the structural response and does not require the extraction of modal components, the method is pa…
On Randomness and Structure in Euclidean TSP Instances: A Study With Heuristic Methods
2021
Prediction of the quality of the result provided by a specific solving method is an important factor when choosing how to solve a given problem. The more accurate the prediction, the more appropriate the decision on what to choose when several solving applications are available. In this article, we study the impact of the structure of a Traveling Salesman Problem instance on the quality of the solution when using two representative heuristics: the population-based Ant Colony Optimization (ACO) and the local search Lin-Kernighan (LK) algorithm. The quality of the result for a solving method is measured by the computation accuracy, which is expressed using the percent error between its soluti…
Surrogate-Assisted Evolutionary Optimization of Large Problems
2019
This chapter presents some recent advances in surrogate-assisted evolutionary optimization of large problems. By large problems, we mean either the number of decision variables is large, or the number of objectives is large, or both. These problems pose challenges to evolutionary algorithms themselves, constructing surrogates and surrogate management. To address these challenges, we proposed two algorithms, one called kriging-assisted reference vector guided evolutionary algorithm (K-RVEA) for many-objective optimization, and the other called cooperative swarm optimization algorithm (SA-COSO) for high-dimensional single-objective optimization. Empirical studies demonstrate that K-RVEA works…
Some Aspects Regarding the Application of the Ant Colony Meta-heuristic to Scheduling Problems
2010
Scheduling is one of the most complex problems that appear in various fields of activity, from industry to scientific research, and have a special place among the optimization problems In our paper we present the results of our computational study i.e an Ant Colony Optimization algorithm for the Resource-Constrained Project Scheduling Problem that uses dynamic pheromone evaporation.
Memetic Algorithms in Engineering and Design
2012
When dealing with real-world applications, one often faces non-linear and nondifferentiable optimization problems which do not allow the employment of exact methods. In addition, as highlighted in [104], popular local search methods (e.g. Hooke-Jeeves, Nelder Mead and Rosenbrock) can be ill-suited when the real-world problem is characterized by a complex and highly multi-modal fitness landscape since they tend to converge to local optima. In these situations, population based meta-heuristics can be a reasonable choice, since they have a good potential in detecting high quality solutions. For these reasons, meta-heuristics, such as Genetic Algorithms (GAs), Evolution Strategy (ES), Particle …
Time optimization and state-dependent constraints in the quantum optimal control of molecular orientation
2014
We apply two recent generalizations of monotonically convergent optimization algorithms to the control of molecular orientation by laser fields. We show how to minimize the control duration by a step-wise optimization and maximize the field-free molecular orientation using state-dependent constraints. We discuss the physical relevance of the different results.
Multiobjective ant colony search algorithm optimal electrical distribution system planning
2005
A dynamic multiobjective, MO, algorithm based on the ant colony search, the multiobjective ant colony search algorithm, MOACS, is presented. The application domain is that of dynamic planning for electrical distribution systems. A time horizon of H years has been considered during which the distribution system are modified according to the new internal (loads) and external (market, reliability, power quality) requirements. In this scenario, the objectives the Authors consider most important for utilities in strategical planning are: the quality requirement connected to the decrease of the expected number of interruptions per year and customer, in the considered time frame, and the choice fo…
Design Optimization Automation for Luminaire Reflectors Using COMSOL Multiphysics and Performance Comparison Against Zemax Opticstudio
2019
This work showcases the complete design pipeline based on COMSOL Multiphysics for one of the luminaire models manufactured by Vizulo. Generation of optimization targets, ray tracing models and utilized optimization algorithms are described. The authors also evaluate the performance of COMSOL against Zemax OpticStudio Premium, a specialized optics design suite widely used by the optics industry. Out-of-the-box version of both packages are tested: ray tracing and optimization performance are compared. It is found that, while OpticStudio' ray tracer is by far superior, OpticStudio is greatly outperformed by COMSOL in optimization tasks for considered problems. Other aspects of both packages ar…