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This paper studies the problem of interdependence between central bank and commercial bank goals. The basic central bank task is to achieve and to maintain price stability. Croatian external debt has been increasing for years and so the activities of the Croatian National Bank are designed to correct this situation. In order to stop the further increase of the external debt, the Croatian National Bank uses several monetary policy instruments, among which is the marginal reserve requirement. On the other hand, the goal of commercial banks is to maximise profits. Banks take loans from abroad at a lower interest rate and invest this money in Croatia at a higher interest rate, thus fulfilling their goal. In order to obtain the desired effects of the marginal reserve requirement, its optimal percentage value should be determined. This problem is modelled as a bi-level mixed 0-1 programming problem. The objective of the leader (Croatian National Bank) is to minimize the increase in household loans by setting different percentages of the reserve requirements for loans extended to households and for those granted to enterprises. The objective of the followers (banks) is to maximize profits. In order to solve this NP-hard problem a heuristic is proposed. In order to verify the model, the paper ends with simulations and the presentation of computational results.

A model for real-time control of flexible manufacturing systems is considered. In this model, a machine can process a finite number of part types at specified rates, but only one part type can be processed at any given time. Each switch from one type to another requires setup time. The clear-the-largest-work-after-setup (CLWS) heuristic policy which stabilizes the system in the sense that, in the long run, the required demand is met, has been introduced. That way, a better upper bound on the total work backlog than those available in earlier literature is derived. Computational results for the case of finite horizon show that the error of the heuristic CLWS from the optimal solution is 2.5–3.0% on average. Some computational results that compare the CLWS heuristic to the heuristic available in the earlier literature, for the same problem, are also reported.