Descent algorithms for discrete resource allocation problems

We consider a class of discrete resource allocation problems, which are hard due to the combinatorial explosion of the discrete search space. In addition, if no dosed-form expressions are available for the cost function of interest, one needs to evaluate or (for stochastic environments) estimate the cost function through simulation. A new approach for such problems (which are typically encountered in discrete event systems), was proposed previously by us (1993). In this paper, we study the deterministic version of the problem and derive necessary and sufficient conditions for a globally optimal solution. A descent algorithm is also presented and it is shown that the algorithm yields a globally optimal allocation.<
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