Search results for "Metaheuristic"
showing 10 items of 153 documents
Hybrid chaotic firefly decision making model for Parkinson’s disease diagnosis
2020
Parkinson’s disease is found as a progressive neurodegenerative condition which affects motor circuit by the loss of up to 70% of dopaminergic neurons. Thus, diagnosing the early stages of incidence is of great importance. In this article, a novel chaos-based stochastic model is proposed by combining the characteristics of chaotic firefly algorithm with Kernel-based Naïve Bayes (KNB) algorithm for diagnosis of Parkinson’s disease at an early stage. The efficiency of the model is tested on a voice measurement dataset that is collected from “UC Irvine Machine Learning Repository.” The dynamics of chaos optimization algorithm will enhance the firefly algorithm by introducing six types of chao…
Principles of scatter search
2006
Scatter search is an evolutionary method that has been successfully applied to hard optimization problems. The fundamental concepts and principles of the method were first proposed in the 1970s, based on formulations dating back to the 1960s for combining decision rules and problem constraints. In contrast to other evolutionary methods like genetic algorithms, scatter search is founded on the premise that systematic designs and methods for creating new solutions afford significant benefits beyond those derived from recourse to randomization. It uses strategies for search diversification and intensification that have proved effective in a variety of optimization problems. This paper provides…
Scheduling projects with limited number of preemptions
2009
A recent paper (Ballestin F, Valls V, Quintanilla S. Preemption in resource-constrained project scheduling. European Journal of Operational Research 2008;189:1136-152) revealed the potential benefits of allowing one interruption when scheduling activities in a resource-constrained project. This paper further investigates the effect of interruption on project length in more general cases. To achieve this, a new model that covers most practical applications of discrete activity preemption is proposed and a metaheuristic algorithm for the problem is developed. Computational experiments on the standard j120 and j30 sets generated using ProGen study the difference in makespan between allowing m …
Optimization of Application-Specific L1 Cache Translation Functions of the LEON3 Processor
2020
Reconfigurable caches offer an intriguing opportunity to tailor cache behavior to applications for better run-times and energy consumptions. While one may adapt structural cache parameters such as cache and block sizes, we adapt the memory-address-to-cache-index mapping function to the needs of an application. Using a LEON3 embedded multi-core processor with reconfigurable cache mappings, a metaheuristic search procedure, and Mibench applications, we show in this work how to accurately compare non-deterministic performances of applications and how to use this information to implement an optimization procedure that evolves application-specific cache mappings.
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…
Variable Neighborhood Search for the Vertex Separation Problem
2012
The vertex separation problem belongs to a family of optimization problems in which the objective is to nd the best separator of vertices or edges in a generic graph. This optimization problem is strongly related to other well-known graph problems; such as the Path-Width, the Node Search Number or the Interval Thickness, among others. All of these optimization problems are NP-hard and have practical applications in VLSI, computer language compiler design or graph drawing. Up to know, they have been generally tackled with exact approaches, presenting polynomial-time algorithms to obtain the optimal solution for speci c types of graphs. However, in spite of their practical applications, these…
Coarse-Grained Barrier Trees of Fitness Landscapes
2016
Recent literature suggests that local optima in fitness landscapes are clustered, which offers an explanation of why perturbation-based metaheuristics often fail to find the global optimum: they become trapped in a sub-optimal cluster. We introduce a method to extract and visualize the global organization of these clusters in form of a barrier tree. Barrier trees have been used to visualize the barriers between local optima basins in fitness landscapes. Our method computes a more coarsely grained tree to reveal the barriers between clusters of local optima. The core element is a new variant of the flooding algorithm, applicable to local optima networks, a compressed representation of fitnes…
Experiences and Future Directions
2003
The development and implementation of metaheuristic procedures usually entails a fair amount of experimentation and reliance on past experiences.
Tabu search with strategic oscillation for the maximally diverse grouping problem
2013
We propose new heuristic procedures for the maximally diverse grouping problem (MDGP). This NP-hard problem consists of forming maximally diverse groups—of equal or different size—from a given set of elements. The most general formulation, which we address, allows for the size of each group to fall within specified limits. The MDGP has applications in academics, such as creating diverse teams of students, or in training settings where it may be desired to create groups that are as diverse as possible. Search mechanisms, based on the tabu search methodology, are developed for the MDGP, including a strategic oscillation that enables search paths to cross a feasibility boundary. We evaluate co…
GRASP with path relinking for the orienteering problem
2014
In this paper, we address an optimization problem resulting from the combination of the well-known travelling salesman and knapsack problems. In particular, we target the orienteering problem, originated in the context of sport, which consists of maximizing the total score associated with the vertices visited in a path within the available time. The problem, also known as the selective travelling salesman problem, is NP-hard and can be formulated as an integer linear program. Since the 1980s, several solution methods for this problem have been developed and applied to a variety of fields, particularly in routing and tourism. We propose a heuristic method—based on the Greedy Randomized Adapt…