| Summary: | Supply Chain (SC) is the effective coordination and integration of all activities performed by several business lines and their infrastructures; such as raw material suppliers, manufacturers, distributors and retailers till delivering the products to the customer.
The supply chain facilities location is an important issue which is needed to be solved as it is one of the important pillars in the supply chain design model. Therefore, it is critical for supply chain managing teams and designers to adopt the latest scientific and most effective methods to locate a facility by carrying different scenarios and trade-offs assessment, the used tools are only a decision supporting tools.
This paper concentrates on the development status of a decision-support tool for solving supply chain design including location problem of various facilities, using the MILP mixed integer linear problem solving programming model by constructing a generic analytical algorithm to solve this problem. EXECL SOLVER TOOL, MATLAB SOFTWARE with a GUI (graphical user input interface) programmed by the C# (C SHARP) programming software are used. In the MILP programming model iterative algorithm methods are used, where every iteration would generate a whole different new set of solutions to match some constrains, conditions and service levels added by the programmer. The first solution only matches some previous added criteria, resulting in a new set of solutions in the iteration, until finally an optimal solution rises under dynamic environment.
In this paper, a typical three layers medium term planning mixed integer linear Programme MILP model for supply chain design is presented and applied for chemicals and biofuel production from rice straw biomass. These three stages are commonly: raw materials collecting areas, distribution center and manufacturing plant locations. With the aid of ASPEN HYSYS simulation software and CAPCOST TOOL, Economic feasibility studies are done for designing supply chain design model. Different scenarios are examined which is a good way to price out potential solutions.
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