In the context of globalization and economic development,customer’s needs are increasing.The whole market is changing from a static market ruled by big companies and manufacturers,to customer-driven market with increasingly high expectations and requirements.Traditionally large-scale production has turned into horizontally integrated,small batch and multivariety production model.Each entity in such a process is trying to make use of its technologies and adapt to the changes providing additional value.On the other hand,they will outsource non-core business activities,and try to utilize external resources,avoiding problems of long cycles and high risks of extensive investments.To succeed,strengthening cooperation and the relationship between suppliers,manufacturers,and sellers have become a necessity.All these participants in the process create a complex supply chain network（SCN）.Traditional manual operations will gradually be replaced by machines and computers.At the same time,under globalization,the national barriers to science and technology will be broken,and the global procurement of equipment and materials will gradually make their costs converge globally,with the supply chain becoming gradually even more complex.No matter how the technology develops in the future,logistics and supply chain activities focusing on optimizing their networks by more cost-efficient facility locations,transportation,warehousing,loading,and unloading will always exist,and the cost of optimizing the supply chain will take a larger portion of overall cost due to diminishing presence of labor.However,the need for cutting costs and increasing efficiency to achieve better performance and increase the profit of supply chains and logistics will grow in its priority,and therefore,SCN planning will play even a bigger role in any organization.Research on the SCN design in the automotive manufacturing industry is in a relatively early phase due to global change of the manufacturing model.Generally speaking,OEMs（Original equipment manufacturers）more and more act as a core company in the automobile supply chain.They work tightly with its suppliers,APMs（auto parts manufacturers）,ordering original,specifically for them designed car parts,which they afterwards assembly into the final product,providing additional value.With the development of automotive OEMs,the APM industry will also grow.As far as APMs are concerned,the planning and layout of their supply chain don’t only have a goal for meeting the requirements of certain OEM anymore.Many of those are becoming giant companies,serving major mainstream automotive OEMs.As a result,their SCN is equally expanding,creating particularly complex systems with an aim to efficiently allocate resources and integrate planning to meet the needs of all customers.Auto parts industry is in its infant state due to significant shifts in the way it operates.Decentralized supply chain and extensive use of third-party logistics providers have affected how the SCNs are designed.Supply of large volumes under strict policies with a high frequency of deliveries also determine a unique planning stage.To this day,not enough research has been done studying the auto part industry and its SCN design.An important factor,particular for a few industries is 100% customer service level.It has been shown that scarce of academic papers have been published incorporating this constraint into the supply chain model.Particularly,there is a lack of such models with an objective to maximize the profit.The modeling of SCN problems and its optimization is a popular topic in many research disciplines.Particularly,the operational research part of academia has dealt with a plethora of real-world network’s challenges,developing solution algorithms and models.Most of the studies related to SCN design are computational,provide new or updated algorithms and study performance of the model solutions.However,the factors and assumptions of the model,due to the nature of the algorithm remain constant.Deficiency of papers regarding research on significant modeling factors and its impact on profit has been noticed.In order to help to fill the identified gap in academic research,this thesis exploits simulation modeling for optimization of SCN and facility location problem（FLP）.The research focuses on recognizing which factors are most significant for modeling through research and actual model development.Most importantly,this thesis tries to give an answer on how does a profit of simulation models perform when significant modeling factors are subject to change while maintaining maximum service level.The goal of the research is to provide a new simulation model whose factors’ variation will identify the impact they have on the profit and could be considered as decision support for future modeling activities.The scope of the research is limited to the strategic level of FLP.Tactical and operational policies and factors are generically provided by the software,giving the best optimal solution,yet,they are not explicitly studied.Inventory safety stock level is used for achieving the desired service level,and under such condition,objective members related to FLP will be studied.The SCN is considered between production plant,ports,transit warehouse facilities and customers.However,the raw material supply and production part of the supply chain are simplified,and focus is on the lower streams of the supply chain.Literature review of this thesis is arranged in a few sections.Firstly,terms related to the SCN are explained,identifying their origins and differences.Secondly,the literature review builds up on to SCN design and levels of decisions it requires to answer.Later facility location with its related FLP is discussed,taking a closer look at its past and current research,definition and classification.Modeling factors in FLP are reviewed,recognizing the most common factors with high significance.Lastly,the characteristics of the supply chain in the auto parts industry have been identified,and its distinctive features differentiated.SCN model,based on the supply chain,is developed to decide the optimal number and physical location of transit warehouses in the European region.Development of the model follows a modeling framework based on the reviewed literature.The data used for the model originate from a real SCN.Several simplifications were made in order to make the computational time reasonable.The most significant one is integrating suppliers’ and production plants’ part of the supply chain into a single node representing one factory.After the conceptualization process,a mathematical model has been developed,which is later translated into a computational model.The model is programmed using software Any Logistix,which utilizes IBM ILOG CPLEX analytical optimization and Any Logic’s Dynamic simulation methods.For generating the facility locations,Greenfield Analysis was carried out,minimizing overall cost flow.Network Optimization experiment,under profit maximization objective,found the optimized solution with a set of constraints deciding for optimal product flows and transportation routes.The simulation of the SCN model with a dynamic estimation of safety stock experiment has helped to allocate resources within the supply chain achieving maximum service level and contributed in the validation of the simulation model.During the simulation model development and continual verification of the model,several factors were established to be significant.Those are arranged into three groups – cost-related,time-related and quantity-related factors.Variation experiments were conducted studying an impact the significant factors have on the profit performance of the supply chain.Sensitivity analysis provided straightforward comparison and quantified intensity of the impact.Production cost and demand factors have shown to be the most influential.Moderately influential factors are transportation cost,inventory carrying cost and processing time,while lightly impacting factors are transportation time,inbound processing cost and outbound processing cost.This thesis focuses on the evaluation of the SCN model and its behavior under factor values variations,and interesting perspectives could be taken from the model for understanding auto parts supply chain and industries with similar characteristics.The generated solution,although it can be used as decision support,it cannot be deployed in the real SCN.Numerous simplifications have been made in order to ensure reasonable time for the computational calculations.Exact ratios and quantified impact on SCN profit are affiliated to the model in this thesis,and it will differ in other networks.Therefore,results are not overly reliable and generalizable,so the reader has to take serious cautions for utilization of the model from the following thesis.Findings have shown certain relations between modeling factors and their impact on the profit,and they were compared mutually by intensity.The efforts SCN has to put on reduction or increment of these factors,however,differ one from another and it is currently unknown.Although the increment of one factor’s parameter might have a bigger impact on the profit,the actual cost and endeavor needed for such accomplishment might result with inefficiency.For that reason,the author recommends further study on efforts needed for a change of modeling factors in relation to their impact on the profit and overall performance of the SCN.