Abstract
This work is aimed at presenting a mathematical model for determining the optimal order in-extenuating conditions (All Unit Discount, Incremental Discount). The expected results are producing several kinds of multi-supplier and multi-time periods with regards to inventories, demand, suppliers' capacity, storage space, and budget constraints in order. It is desirable to minimize the purchasing costs, storage and ordering while considering the lack of needed materials at specified times. To confirm the efficiency of the proposed model in solving purchase planning problems in real world, it has been applied in Asian Oil Turbo Compressor Design Corporation and received approval from the obtained results and experts’ comments. To solve the designed model, the GAMS software is used. Also, model sensitivity analysis and usable results in management decision making based on the importance of proposed matters (shortage reduction in each period and demand increase effect on final cost) are then presented.
Highlights
The direct and indirect impacts of inaccurate decision makings regarding the choice of suppliers and the order quantity are observed more strongly and vitally with the ever increasing dependence of organizations on their suppliers
The main objective of this paper is the development of an appropriate model to determine the optimal order quantity and minimize the shortage, total material purchase, storage and ordering costs considering the terms of the whole unit and incremental discounts
Gray and white colors indicate all unit and incremental discounts offered by the suppliers, respectively
Summary
The direct and indirect impacts of inaccurate decision makings regarding the choice of suppliers and the order quantity are observed more strongly and vitally with the ever increasing dependence of organizations on their suppliers. Due to the NP-hardness of the problem, the hybrid algorithm model has been used to solve it Considering such factors as accumulated size for several suppliers, multi-period ordering and all unit discounts, Amy et al have developed a mixed, integrated planning model to minimize total expenses such as ordering, storage, purchase and transportation costs and used the genetic algorithm to solve it [4]. Kokangula et al have used a combination of AHP model, integer, linear and multi-objective planning to determine the order quantity for each of the suppliers by considering constraints such as all unit discount, capacity and budget [17]. A planning model has been developed to minimize the costs of purchase under discount conditions, storage, order and expense shortage, considering the problem objectives and order assignment to suppliers.
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