Now showing items 1-6 of 6
Ant algorithms with immigrants schemes for the dynamic vehicle routing problem
Many real-world optimization problems are subject to dynamic environments that require an optimization algorithm to track the optimum during changes. Ant colony optimization (ACO) algorithms have proved to be powerful ...
Ant colony optimization with immigrants schemes for the dynamic railway junction rescheduling problem with multiple delays
Train rescheduling after a perturbation is a challenging task and is an important concern of the railway industry as delayed trains can lead to large fines, disgruntled customers and loss of revenue. Sometimes not just one ...
Ant colony optimization with self-adaptive evaporation rate in dynamic environments
(IEEE Press, 2014-12)
The performance of ant colony optimization (ACO) algorithms in tackling optimization problems strongly depends on different parameters. One of the most important parameters in ACO algorithms when addressing dynamic ...
Metaheuristics for dynamic combinatorial optimization problems.
(The Institute of Mathematics and its Applications., 2012)
Many real-world optimization problems are combinatorial optimization problems subject to dynamic environments. In such dynamic combinatorial optimization problems (DCOPs), the objective, decision variables and/or constraints ...
Applying ant colony optimization to dynamic binary-encoded problems
Ant colony optimization (ACO) algorithms have proved to be able to adapt to dynamic optimization problems (DOPs) when stagnation behaviour is addressed. Usually, permutation-encoded DOPs, e.g., dynamic travelling salesman ...
A memetic ant colony optimization algorithm for the dynamic travelling salesman problem.
Ant colony optimization (ACO) has been successfully applied for combinatorial optimization problems, e.g., the travelling salesman problem (TSP), under stationary environments. In this paper, we consider the dynamic TSP ...