جستجوی مقالات مرتبط با کلیدواژه « برنامه ریزی خطی عدد صحیح » در نشریات گروه « صنایع »

Sohrabi and Nalchigar (1389), proposed a new data envelopment analysis (DEA) model to identify the most efficient decision making unit (DMU) considering imprecise data. In this paper it will be shown that the proposed model is not able to determine the most efficient DMU and the model randomly introduced an efficient DMU as the most efficient. It will be shown also that the proposed model to determine the most efficient DMU in the case of variable return to scale have the same drawback and also may be infeasible in some cases. To overcome the drawbacks new integrated models will be presented. In addition, to find and rank other most efficient DMUs an algorithm will be proposed. By using the presented model in the paper decision maker can find the most efficient DMU by solving only one linear integer programming. Applicability of proposed model is indicated by using imprecise data set includes specifications of 18 suppliers.

In this paper, a hybrid method for limited resource allocation and leveling in complex multi-stage, multi-product and multi-period production planning problems with aim of lot-size determination and total cost minimization has been proposed. This problem consists of multiple products with sequential production processes that are produced in different periods to meet the customers demand. By determining decision variables, production capacity of machines and customers demand, an integer linear program is developed to minimize the total set-up, inventory holding and production cost. A three-stage approach has been developed to solve the problem. In the first stage, the primary problem is divided into several sub-problems using a heuristic algorithm based on the limited resource Lagrangean multipliers. In this case, each sub-problem could be solved using more simple methods. In the second stage a new approach is proposed to solve these sub-problems combining the genetic algorithm with a neighborhood search technique. In the third stage resource leveling is performed among sub-problems to obtain a better solution. In this case, lot-size for each product is determined during the planning periods. This paper's objectives have been evaluated and verified through several empirical experiments.