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A multi-agent model for optimizing supermarkets location in emerging countries

We propose a simple location model taking into account an existing traditional market and the increasing attractiveness of urban consumers for supermarkets in Hanoi city. The foundation of this model is based on sociological studies on consumer perception of supermarkets in this city. We represented the purchase decision-making rule based on various criteria such as the agent's incomes, the product quality levels and the points-of-sales distances from their home. We built a multi-agent model simulating the consumer's choices between many traditional markets and a new local supermarket to optimally localize. Thanks to the Particle Swarm Optimization heuristic, the model iteratively determines a place maximizing the sales volume of the new supermarket. Some interesting results can help the decider to choose a price policy as well as a product quality level according to existing point-of-sales locations.