Modeling Supply Chain Network under Risk and Uncertainty

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Date

2017-06

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Addis Ababa University

Abstract

Supply Chain network design (SCND) is a principle emphasizing the utilization of an efficient integrated system of suppliers, producers, warehouses, retailers and customers, so that items can be produced and distributed system-wide at the right quantities and right locations so as to minimize costs and maximize services. It deals with strategic decisions such as deciding on the number, location, capacities and technologies of facilities to be opened, changes to existing facilities and supplier as well as wholesaler or customer selection. In addition it includes tactical decisions such as production, shipping plans and material flow through the network. The supply chains are complex, dynamic and highly uncertain. Uncertainty in supply chain may take in the form of demand uncertainty(inaccurate forecasting, seasonality, changes in customer preferences, etc.), supply uncertainty(e.g. supply yields, supply capacities, etc.). Underestimating the impact of uncertainties of supply chain and optimizing under the assumptions of deterministic parameters is risky. Uncertainties of supply chain should be explicitly included in the decision making process. In this paper, a stochastic single objective optimization model have been considered for the supply chain network optimization problem under risk and uncertainty and finally cost effective supply chain network is forwarded. This thesis address the design of four echelon (supplier, plants, warehouse and wholesaler) supply chain network(SCN), where both the plant‟s supplier and customer demand are considered to be uncertain and stochastic but other parameters are deterministic and known in advance. This paper proposes a single objective-single product optimization model for handling the inherent uncertainties in the forward supply chain for designing the supply chain network problem. A linear programming(LP) model is applied to realize the design of supply chain network problem effectively. First a survey questionnaire on the existence of risk and uncertainty to the Ethiopian textile industries, found in Addis Ababa, have been conducted so as to have contextual meaning on the literature review towards the Ethiopian textile industries context. Then the survey has been analyzed in a way that can be understandable clearly so that risks to be taken into the model has been prioritized based on the respondent rate and finally these with high respondent rate have been modeled into the transportation cost minimization problem, which considers the shipment cost per kg and capacity(quantity) in kg.General Algebraic Modeling System (GAMS 24.8.3) is used as a tool to formulate and solve the LP model. A case study of Yirgalem Addis textile factory PLC is taken to demonstrate the validity of the model. By evaluating the output data, the supply chain network for this case is designed and the optimal product flow and or material flow between the suppliers, plant, warehouse and wholesalers is calculated. The result of the optimization model is compared to the existing transportation cost of the case company and by the application of this model about 9% annual cost reduction is achieved. Finally a sensitivity analysis of the supply and demand uncertainty have been conducted to illustrate their impacts on the expected minimum cost. The result of the sensitivity analysis shows that the suggested network diagram has a consistency to tolerate the variations in demand and supply uncertainty. This contradicts with the case of the deterministic environments in a way that, the variation in demand and supply will cause the network structure and this requires another network development. Optimization of the supply chain network has great importance in the case of stochastic environment in such a way that, the developed network is tolerable to the demand and supply uncertainty and risk. If there is a variation in the supply and demand, the suggested network diagram will not fail easily, it has the ability to resist these variations of demand and supply uncertainty. Therefore the author concludes that, optimization of the supply chain network under the assumption of deterministic feature of supply and demand is risky and this may cause to the uncertainty of the supply chain structure.

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Keywords

SCND and uncertainty, supply chain network optimization, Linear Programming(LP), Yirgalem Addis Textile factory PLC, GAMS build system

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