1. An automated computerized method for optimizing allocation of a set W of n tasks to m available resources for accomplishing such tasks using combinatorial multimodal optimization for finding multiple optimal ways of dividing said set W of n tasks task values into m respective groups associated with said available resources, such that each of the groups satisfies a respective constraint condition, said method comprising: using at least one computer to execute a computer program to automatically perform a series of machine operations comprising: (a) receiving digital data signals representing plural tasks for assignment to said available resources and, based thereon, defining an initial population of trial solutions representing multiple optional ways of dividing the set W of n tasks between said m resources; (b) calculating for each trial solution a fitness vector comprising m elements, each of which is indicative of whether the constraint condition of a corresponding respective one of the m groups has been satisfied by the trial solution; (c) selecting a plurality of trial solutions for a next generation in dependence upon their respective fitness vectors; (d) creating a new population of trial solutions including the selected earlier trial solutions; (e) repeating steps (b) to (d) until the population of trial solutions stabilizes, the individual trial solutions of the stable population representing multiple optional ways of dividing the set W of n tasks to said m resources; and (f) outputting data representing at least one of the individual trial solutions of said stabilized population as an optimized allocation of tasks to resources.