ASSESSMENT AND CREATION OF LIVESTOCK SUPPLY CHAIN MANAGEMENT
ASSESSMENT AND CREATION OF LIVESTOCK SUPPLY CHAIN MANAGEMENT
Turkey, including different climate structures, the presence of a variety of animals from different species and breeds and a large part of population still living in rural areas, is in a position that livestock issues should be given specific attention. However, in recent years, in the share of total agricultural production, animal production increased steadily in all developed countries, such an increase could not be achieved in Turkey. Since the beginnings of 2000's meeting the demand for more individual based products, customer specific product variants and shortest delivery times has increased their significance. In the process of examining the different parameters of mass customization and mass production, simulation techniques are able to be utilized to understand that which way have to be chosen. A livestock management framework is created and basically simulated under some specific criteria based on the paradigm shift of mass customization. This simulation is going to own an environment and agents, and these agents have to take their own decisions randomly to obtain much objective results. Therefore, an agent-based simulation approach need to be done in here. Livestock supply chain constitutes the main part of the livestock management, so the simulation basically works under the circumstances of the properties of this supply chain. The parameters can be expressed such as centralization & decentralization, environmental effects, complexity, customer satisfaction, product variation, democratization of design and open innovation, market and customer proximity, usage of resources, regionalism and authenticity, energy saving, sustainability. The condition and parameters of supply chain, environment and the agents are able to change to obtain specific results for different parameters of mass customization. Due to these changes, design of experiment have to be made for levels of the parameters to find the optimum condition.
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