Strategies for Resource Allocation of Two Competing Companies using Genetic Algorithm
This work addresses resource allocation for companies in competitive retail environments, but it is incremental as it applies existing methods to a specific domain.
The study tackled the problem of optimizing shop locations for market dominance between two competing supermarket chains using a two-dimensional Ising model, finding that initial configurations with specific topological properties evolve faster to dominance in simulations.
We investigate various strategic locations of shops in shopping malls in a metropolis with the aim of finding the best strategy for final dominance of market share by a company in a competing environment. The problem is posed in the context of two competing supermarket chains in a metropolis, described in the framework of the two-dimensional Ising model. Evolutionary Algorithm is used to encode the ensemble of initial configurations and Monte Carlo method is used to evolve the pattern. Numerical simulation indicates that initial patterns with certain topological properties do evolve faster to market dominance. The description of these topological properties is given and suggestions are made on the initial pattern so as to evolve faster to market dominance.