Now showing items 1-10 of 35
Memory-based multi-population genetic learning for dynamic shortest path problems
(IEEE Press, 2019-06)
This paper proposes a general algorithm framework for solving dynamic sequence optimization problems (DSOPs). The framework adapts a novel genetic learning (GL) algorithm to dynamic environments via a clustering-based ...
Adapting the pheromone evaporation rate in dynamic routing problems
An ant system with direct communication for the capacitated vehicle routing problem.
(University of Manchester., 2011)
Ant colony optimization with memory-based immigrants for the dynamic vehicle routing problem.
A recent integration showed that ant colony optimization (ACO) algorithms with immigrants schemes perform well on different variations of the dynamic travelling salesman problem. In this paper, we address ACO for the dynamic ...
Empirical study on the effect of population size on MAX-MIN ant system in dynamic environments
(IEEE Press, 2016-07)
In this paper, the effect of the population size on the performance of the MAX -MIN ant system for dynamic optimization problems (DOPs) is investigated. DOPs are generated with the dynamic benchmark generator for ...
Benchmark Generator for the IEEE WCCI-2014 Competition on Evolutionary Computation for Dynamic Optimization Problems: Dynamic Rotation Peak Benchmark Generator (DRPBG) and Dynamic Composition Benchmark Generator (DCBG)
(De Montfort University, UK, 2013-10)
Based on our previous benchmark generator for the IEEE CEC’12 Competition on Dynamic Optimization, this report updates the two benchmark instances where two new features have 1been developed as well as a constraint to the ...
A survey of swarm intelligence for dynamic optimization: Algorithms and applications
Swarm intelligence (SI) algorithms, including ant colony optimization, particle swarm optimization, bee-inspired algorithms, bacterial foraging optimization, firefly algorithms, fish swarm optimization and many more, have ...
An immigrants scheme based on environmental information for ant colony optimization for the dynamic travelling salesman problem.
Ant colony optimization (ACO) algorithms have proved to be powerful methods to address dynamic optimization problems. However, once the population converges to a solution and a dynamic change occurs, it is difficult for ...