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—A key parameter affecting the operation of differential evolution (DE) is the crossover rate Cr ∈ [0, 1]. While very low values are recommended for and used with separable problems, on non-separable problems, which include most real-world problems, Cr = 0.9 has become the de facto standard, working well across a large range of problem domains. Recent work… (More)

Ant Colony Optimisation based solvers systematically scan the set of possible solution elements before choosing a particular one. Hence, the computational time required for each step of the algorithm can be large. One way to overcome this is to limit the number of element choices to a sensible subset, or candidate set. This paper describes some novel… (More)

Many animals use chemical substances known as pheromones to induce behavioural changes in other members of the same species. The use of pheromones by ants in particular has lead to the development of a number of computational analogues of ant colony behaviour including Ant Colony Optimisation. Although many animals use a range of pheromones in their… (More)

—In the commonly used DE/rand/1 variant of differential evolution the primary mechanism of generating new solutions is the perturbation of a randomly selected point by a difference vector. The newly selected point may, if good enough, then replace a solution from the current generation. As the magnitude of difference vectors diminishes as the population… (More)

Constructive metaheuristics explore a tree of constructive decisions, the topology of which is determined by the way solutions are represented and constructed. Some solution representations allow particular solutions to be reached on a greater number of paths in this construction tree than other solutions, which can introduce a bias to the search. However,… (More)

Production scheduling problems such as the job shop consist of a collection of operations (grouped into jobs) that must be scheduled for processing on different machines. Typical ant colony optimisa-tion applications for these problems generate solutions by constructing a permutation of the operations, from which a deterministic algorithm can generate the… (More)

Each particle of a swarm maintains its current location and its personal best location. It is useful to think of these personal best locations as a population of attractors. When this population of attractors converges, the explorative capacity of the swarm is reduced. The convergence of attractors can occur quickly since the personal best of a particle is… (More)

When using a constructive search algorithm, solutions to scheduling problems such as the job shop and open shop scheduling problems are typically represented as permutations of the operations to be scheduled. The combination of this representation and the use of a constructive algorithm introduces a bias typically favouring good solutions. When ant colony… (More)

Standard particle swarm optimization cannot guarantee convergence to the global optimum in multi-modal search spaces, so multiple swarms can be useful. The multiple swarms all need initial positions and initial velocities for their particles. Several simple strategies to select initial positions and initial velocities are presented. A series of experiments… (More)