Impact of information sharing in hierarchical supply chain decision-making framework

This paper analyzes the impact of information sharing in four-level hierarchical decision-making framework of supply chains. The process plan selection and real-time resource allocation problems at each level in the hierarchy are solved by separate multi-objective genetic and simulated annealing algorithms. The sources of information affecting the achievement of best possible decisions are then identified at each decision level, and the extent of their effects from sharing them are analyzed in terms of the degree and the content of information. The generality and validity of the proposed approach are successfully tested for diverse manufacturing systems generated from a designed experiment.