integer nonlinear programming

Inventory overhead is one of the costly elements in many organizations. With globalization trends and increase in competition, customers expect to receive their commodities quickly; therefore, inventory management has become a key factor to remain in today's competitive business. Despite extensive researches in this eld, there is a signicant gap between real-world problems and existing academic researches. Batch production and shipment is one of the main concerns in production systems and inventory control models. This concern stems from real world cases where the system has items manufactured in batches with a known size, for instance production of bottle caps by cap compression molding machines and so forth. Initial eorts to use mathematical approaches in order to gure out inventory problems, begin as well as producing industries and other engineering elds. Necessity of resolving inventory problems is recognized in some industries that involve combination of producing management problems and inventory problems, in fact they have produced accumulation of items and products and cost of setup machines are quiet expensive. In the beginning of the twentieth century, two of the primary mathematical inventory models called the economic order quantity and economic production quantity were presented. In this study, an eective, simple and practical algorithm is represented to solve proposed non-linear integer programming problem. The proposed model formulates an economic production quantity inventory control system consists of a company and a supplier, that receive discrete deliveries orders. In this paper, a previous published work is improved and formulated without constraints. Then, unconstrained model is solved using an improver algorithm involving four simple steps. In this paper, the previously published model is being modied with less constraints and decision variables, in order to nd a better solution with less computational time using the proposed heuristic. So, numerical example of previously published paper is solved employing improver algorithm, and the better solution obtained is shown. Finally, the eciency of this algorithm was shown many comparisons to the previously published algorithm.