Abstract
In this study, a multi-objective mathematical model is developed to optimize the distribution network in a three level supply chain based on the inventory location- models with the aim of locating distribution centers. also, appropriate allocation of customers in order to maximize coverage of the demand, ...
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In this study, a multi-objective mathematical model is developed to optimize the distribution network in a three level supply chain based on the inventory location- models with the aim of locating distribution centers. also, appropriate allocation of customers in order to maximize coverage of the demand, increasing sales through discount policies and ultimately improving the transportation system by selling the package of products agaainst individual sales is considered.On the other hand, the policy of selling pakages, Increases the total sales and their profit margin by creating appropriate price for the customrers. Due to the circumstances, each distribution center has specific reliability level which the proposed model try to maximize it. In order to make the model more realistic, some parameters have been considered under conditions of uncertainty and robust planning techniques have been used to solve it, finally, to validate the presented model, and instance according to real-world problems were solved by GAMS software. The Results are presented in details
Mehran Khalaj; Amir Hossine Khalaj; Jalal Talebi
Abstract
Manufacturing systems are always facing different kinds of risk such as failure and interruption risk. Performance risk analysis of manufacturing systems cause errors happening in the prediction of parameters and will also result in wrong decisions where the real and appropriate data is not available. ...
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Manufacturing systems are always facing different kinds of risk such as failure and interruption risk. Performance risk analysis of manufacturing systems cause errors happening in the prediction of parameters and will also result in wrong decisions where the real and appropriate data is not available. In uncertainty condition there is no appropriate data for decision making and in the specific mode of uncertainty the decision maker faces with a lack of information. Risk is a state of uncertainty that the available information from background of system is incomplete. Risks in manufacturing systems are directly related with failure to achieve the reliability of machines. So in this paper the records and the relationship between risk and reliability have been studied, then a model is proposed using Dumpster-Shafer theory to maximize the reliability according to the existing risk. Since the exact calculation of reliability for complex systems and processes is extremely difficult and complicated when the correct data of failure is not available, newly proposed model uses Dumpster-Shafer theory that enjoys all the available data for decision making instead of using the purely qualitative methods. Using this method results in obtain the risk ranges for equipment and machinery. These ranges are drawn in a risk analysis matrix according to the relationship between risk and reliability of machinery and the changes have been determined in order to meet the lower risk. All the proposed methods are examined using the data of a manufacturing company, the concentration of evaluating the reliability is on using the Probability theory in which the failure time is predicted by determining type of component failure distribution while the research provides change in attitude for applying the simultaneous use of possibility and probability theory
