Abstract
Organizations are often facing the problem of determining the degree of investment in building information links with their suppliers and buyers to reduce costs, lead times, and quality problems, improve timely customized delivery, increase asset utilization and improve corporate profitability. One of the critical enablers for an efficient and effective supply chain is timely planning and information processing across the entire value-added chain. This paper presents an integer programming formulation for selecting the right mix of analytical software and hardware alternatives at various planning and execution levels necessary for an organization to remain competitive in a supply chain. The qualitative factors such as quality, reliability, flexibility, timeliness and organizational compatibility that are of utmost importance in supply chain management have been quantified into cost components that form the weighted cost function. The weights of the various cost components of software and hardware are the eigen vectors derived from pair-wise comparison. These weights take care of the relative importance of alternative supply chain strategies for an organization. The objective functions and the constraints have been linearized in order to alleviate the computational complexity of the model. The proposed framework has been tested for its computational complexity and the corresponding sensitivity analysis has been carried out and the computational experience has been reported.
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