A mixed neural-genetic algorithm for the broadcast scheduling problem

Abstract

The broadcast scheduling problem (BSP) arises in frame design for packet radio networks (PRNs). The frame structure determines the main communication parameters: communication delay and throughput. The BSP is a combinatorial optimization problem which is known to be NP-hard. To solve it, we propose an algorithm with two main steps which naturally arise from the problem structure: the first one tackles the hardest contraints and the second one carries out the throughput optimization. This algorithm combines a Hopfield neural network for the constraints satisfaction and a genetic algorithm for achieving a maximal throughput. The algorithm performance is compared with that of existing algorithms in several benchmark cases; in all of them, our algorithm finds the optimum frame length and outperforms previous algorithms in the resulting throughput.

Assignment of cells to switches in a cellular mobile network using a hybrid Hopfield network-genetic algorithm approach

“…Note that the updating rule only takes into account neurons x pq with value 1 and within a distance of c ip in columns of the element x ik being updated [12,13]. The matrixĈ is an n  n matrix which encodes the problem's constraints given by Eq.…”

“…(7). Its elements are defined as follows: (12) Note that this matrix forces one and only one 1 per row, whereas there may be several 1s in the same column.…”

Hybrid meta-heuristics algorithms for task assignment in heterogeneous computing systems

“…The dynamics of this network depends on a matrix C which defines the minimum distance between two 1 s in the network for each row, and on the initial state of the neurons. See [18][19][20] for further details. The structure of the HNN can be described as a graph, where the set of vertices are the neurons, and the set of edges define the connections between the neurons.…”

Meta-Heuristic Algorithms for FPGA Segmented Channel Routing Problems with Non-standard Cost Functions

“…Other previous approaches to combinatorial optimization problems using a hybrid scheme Hopfield Network-Genetic Algorithm are the works by Watanabe et al [27], Balicki et al [2], Bousoño-Calzón et al [3] and Salcedo-Sanz et al [21].…”