  Supply chain management is a very dynamic operation research problem where
one has to quickly adapt according to the changes perceived in environment in
order to maximize the benefit or minimize the loss. Therefore we require a
system which changes as per the changing requirements. Multi agent system
technology in recent times has emerged as a possible way of efficient solution
implementation for many such complex problems. Our research here focuses on
building a Multi Agent System (MAS), which implements a modified version of
Gravitational Search swarm intelligence Algorithm (GSA) to find out an optimal
strategy in managing the demand supply chain. We target the grains distribution
system among various centers of Food Corporation of India (FCI) as application
domain. We assume centers with larger stocks as objects of greater mass and
vice versa. Applying Newtonian law of gravity as suggested in GSA, larger
objects attract objects of smaller mass towards itself, creating a virtual
grain supply source. As heavier object sheds its mass by supplying some to the
one in demand, it loses its gravitational pull and thus keeps the whole system
of supply chain per-fectly in balance. The multi agent system helps in
continuous updation of the whole system with the help of autonomous agents
which react to the change in environment and act accordingly. This model also
reduces the communication bottleneck to greater extents.
