Maximizing revenue in omnichannel grocery retailing through store assignment for fulfilling online orders

In the evolving landscape of omnichannel grocery retailing, companies aim to optimize customer service by blending traditional and digital channels. This study focuses on the Buy-Online-and-Pick-up-in-Store (BOPS) strategy, which is crucial for this integration, providing customers with the convenience of online shopping with physical store pick- ups. Effective BOPS relies on strategically chosen store locations for fulfilling online orders. We introduce a novel model using feedforward neural network (NN) and particle swarm optimization (PSO) algorithms, aiding retailers in selecting suitable store locations. Through a real-world application, we show that our model yields store allocation decisions that improve revenue in omnichannel retailing.