چكيده به لاتين
In recent years, researchers and senior executives of manufacturing companies have shown particular attention to resilient supply chain, crisis management and disaster management. In this regard, an integrated approach to resilient supply network design will be provided under uncertainty of market demand and demand market disruptions.
For this purpose, a multi-stage, single-product, multi-period, and three-level model (manufacturers, distributors, and customers) is proposed as a mixed integer nonlinear programming model. The objectives of the problem are to maximize the chain's profit and minimize the total amount of time considered, including the time when the goods are sent between the facility and the time of the marketing and advertising activities. Hence, using the Epsilon-Constraint method, a set of answers is obtained for profit and time goals. Through the choices of the decision maker, a couple of these answers are selected.
The uncertainty conditions in this problem are affected by the demand for each market, so that only the upper and lower limits of the uncertain parameters are known and certain. Also, the amount of funds considered for advertising and marketing activities and the timing of these activities is different based on the disrupted scenarios. Due to the reduction of the exchange rate and, consequently, the decline in the purchasing power of people, the entry of rival companies into the market and the other reasons like this, market demand will suffer from cyclical downturns. Also due to the occurrence of destructive events such as floods, earthquakes, terrorist incidents and ..., manufacturing companies will fall sharply in demand at some point in time. Resilience strategies such as marketing and advertising activities and finding new demand markets are being taken to address these system and environmental uncertainties. By sending goods between distributors, in times of crisis, we will seek to reduce lost sales costs and inventory costs. Approaches such as nominal / expected value approach, Stochastic programming and stochastic-Robust programming Based on Scenario used in the face of these uncertainties. The two objective programming model provided by the GAMS software is solved using the CPLEX solver. In order to explain the performance of the proposed model, a case study has been carried out at Steel Alborz's company. The behavior of the proposed model is analyzed in both deterministic and Robust conditions for different states of uncertain conditions. The results show the efficiency and effectiveness of strategies for finding a new market in the event of a crisis, an estimated 10 percent increase in total profits. Also, the results indicate that the Robust method is superior to other methods used.
Keywords: supply chain network design, disturbance on demand market, resilency, lateral transshipment, robust optimization approach, e-constraint method.
