Abstract:

With the layout of the omni-channel marketing strategy, the number of consumers in the omni-channel witnesses an explosive growth, and the consumer behavior of the omni-channel becomes a research hotspot. However, the consumption data of the omni-channel consumers of the chain retail supply chain is massive and high dimensional. Given the abovementioned features, we propose a co-evolution algorithm to analyze omni-channel consumer behavior in the chain retail supply chain. Taking the advantages of the particle swarm optimization algorithm and adaptive genetic algorithm, the two populations are traversed simultaneously, and the information interaction mechanism is introduced between the two populations, which makes the two populations collaboratively evolve. Empirical research proves that when the collaborative  evolution algorithm is applied to association rule mining of omni-channel consumer’s consumption data in the chain retail supply chain, the speed of the algorithm is faster, and it can also avoid the local optimum of the genetic algorithm when it is applied alone, and improves the quality of omni-channel consumer behavior association rule mining in the chain retail supply chain . It provides a new method for the study of the omni-channel consumer purchasing behavior.

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