RandomBipartiteGraph(n, p) creates an undirected unweighted bipartite graph on n vertices where each possible edge is present with probability p.

RandomBipartiteGraph(n, m) creates an undirected unweighted bipartite graph on n vertices and m edges where the m edges are chosen uniformly at random.

RandomBipartiteGraph([a,b], p) creates an undirected unweighted bipartite graph on a+b vertices with partite sets of sizes a and b, where each possible edge is present with probability p.

RandomBipartiteGraph([a,b], m) creates an undirected unweighted bipartite graph on a+b vertices with partite sets of sizes a and b, and with m edges chosen uniformly at random.

If the option weights=m..n is specified, where m <= n are integers, the graph is a weighted graph with edge weights chosen from [m,n] uniformly at random.  The weight matrix W in the graph has datatype=integer, and if the edge from vertex i to j is not in the graph then W[i,j] = 0.

If the option weights=x..y where x <= y are decimals is specified, the graph is a weighted graph with numerical edge weights chosen from [x,y] uniformly at random.  The weight matrix W in the graph has datatype=float[8], that is, double precision floats (16 decimal digits), and if the edge from vertex i to j is not in the graph then W[i,j] = 0.0.

If the option weights=f where f is a function (a Maple procedure) that returns a number (integer, rational, or decimal number), then f is used to generate the edge weights.  The weight matrix W in the graph has datatype=anything, and if the edge from vertex i to j is not in the graph then W[i,j] = 0.

The random number generator used can be seeded using the randomize function.